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Digital signal processing: Handbook
Abstract
The fundamentals of the theory and design of systems and devices for the
digital processing of signals are presented. Particular attention is
given to algorithmic methods of synthesis and digital processing
equipment in communication systems (e.g., selective digital filtering,
spectral analysis, and variation of the signal discretization
frequency). Programs for the computer-aided analysis of digital filters
are described. Computational examples are presented, along with tables
of transfer function coefficients for recursive and nonrecursive digital
filters.
... The expectation in (38) is implemented in the form of time averaging. In particular, the time averaging is performed per frequency subchannel and per noise stationary temporal region over the OFDM blocks that belong to that region. ...
... The first stage is to estimate the noise statistical properties, namely the cyclic auto/cross-correlations matrices for the time-domain techniques and spatial-correlation matrices for the frequency-domain technique. In particular, the cyclic auto/cross-correlation is computed using (43a) while the spatial-correlation per OFDM frequency sub-channel is computed using (38) and (39). In the second stage, we run the Monte Carlo simulation for the end-to-end NB-PLC system for different SNR values. ...
... Two main representations are commonly used to analyze the cyclostationary signals as described in [33] and [38]: Decimated Components and Subband Components. In the Decimated Components representation, the cyclostationary process x[n] with a period P is represented as P different stationary processes x i [n] = x[nP + i], i = 0, . . . ...
The cyclostationary noise in narrowband powerline
communications (NB-PLC) severely degrades the system’s reliability.
Considering single-input multi-output (SIMO) transmission,
in this paper, we exploit the NB-PLC noise cyclostationarity
and high spatial correlation across multiple receive phases to
design practical and efficient noise mitigation techniques. In particular,
we propose two time-domain-based cyclostationary signal
recovery techniques, with different performance and complexity
levels, that take into consideration the joint cyclostationarity
of both the NB-PLC noise and the orthogonal frequency division
multiplexing-modulated information signal across multiple
receive phases. In addition, we propose a frequency-domainbased
noise mitigation technique that exploits knowledge of the
noise power spectral density as well as the cross-correlation
per frequency subchannel over the different receive phases. The
proposed SIMO NB-PLC noise mitigation techniques are shown
via simulation results conducted using field noise measurements
to achieve considerable performance gains over a single-input
single-output receiver.
... In order to simplify analysis, it is assumed that the RX provides the decoder with an artificially delayed version of the reconstructed signal, i.e., y[n − n 0 ], where n 0 = 0 or 1 with equal probability. This is obviously an informationlossless operation, which has no effect on the statistics of the first two WSS terms of the right-hand side of (1), however, it transforms w[n] to a WSS process [8], whose PSD can be shown to be equal to ...
... Unfortunately, in contrast to C1 that can be implicitly imposed in the design by simply using (8) in the CMSE formula, C2 must be explicitly imposed in the numerical search for the optimal TX FB. Since CMSE is a non-linear and non-convex function of filter responses, this makes the search for a good design difficult, in addition to computationally intensive. ...
... In this design, the RX FB is matched to the TX FB as F k (e iω ) = e −iωN H * k (e iω ), k = 0, 1. This choice is in line with C1 as long as the TX FB satisfies (8), and introduces a symmetry of TX and RX FB magnitude responses. This symmetry is natural, e.g., in a communication setting where the same FB acts as TX as well as RX FB, as in a TDMA communication. ...
... The density of spectral correlation is described by the cyclic spectra which are the Fourier transforms of the cyclic autocorrelation functions [110,Chap. 12], [113], [120], [131], [159]. ...
... ACS processes are appropriate models for signals in several fields such as telecommunications, radar, sonar, telemetry, mechanics, acoustics, climatology, biology, econometrics, and astronomy [110,Chap. 12], [113], [120], [131], [159]. In communications and radar/sonar, almostcyclostationarity properties have been exploited for a variety of applications. ...
... 3.3.2], [131], [247]. ...
A concise survey of the literature on cyclostationarity of the last 10 years is presented and an extensive bibliography included. The problems of statistical function estimation, signal detection, and cycle frequency estimation are reviewed. Applications in communications are addressed. In particular, spectrum sensing and signal classification for cognitive radio, source location, MMSE filtering, and compressive sensing are discussed. Limits to the applicability of the cyclostationary signal processing and generalizations of cyclostationarity to overcome these limits are addressed in the companion paper ``Cyclostationarity: Limits and generalizations''.
... The main objective of spectrum estimation is the determination of the power spectral density (PSD). According to the [9], periodogram can be obtained by first estimating the autocorrelation sequence from the observed samples 0 , 1 , … , 1 and applying the Discrete Time Fourier Transform (DTFT) to these estimates. Usually the periodogram is calculated by applying the FFT. ...
... It is necessary to find the periodogram of each segment and then calculate the average value over all periodograms. The Bartlett method can by expressed by [9]: 1 ...
... The reduction of variance leads to decrease of resolution. The method based on Bartlett estimation has times smaller resolution than the method of periodogram [9]. ...
This paper deals with real time implementation of spectrum sensing method used for detection in TV bands. The most common and simplest method of spectrum sensing is based on the energy detection principle (using Periodogram, Bartlett and Welch methods). Intermediate frequency band signal of TV receiver was used in real-time implementation. The main algorithm was implemented on the Memec Development Board with FPGA Virtex IV and with A/D (D/A) converters assembled on analogue module P240. Humax F3-FOX T was chosen as a television receiver. Our results were compared with Matlab simulations based on the same input signals. It shows that we can detect free spaces in the TV channels. The real time realization can be used as an important part of Cognitive Radio chain.
... As shown in [2][3][4] one of the most widespread digital signal processing algorithms is digital filtering. At present digital filters are widely applied in receivers embedded in different software-defined systems. ...
... In [3,4] it is shown that digital FIR-filters with linear phase are widely used in practice [9]. There are four types of FIRfilters with linear phase, which are different from each other by the symmetry of impulse response and evenness of filter order N [3]: 1 st type -N is odd and the impulse response is symmetric, 2 nd type -N is even and the impulse response is symmetric, 3 rd type -N is odd and the impulse response is antisymmetric, 4 th type -N is even and the impulse response is anti-symmetric. ...
The paper is devoted to modular digital filters including their use in hydroacoustic monitoring tasks. We describe software-defined technology. We provide the description of hydroacoustic monitoring tasks where modular filter application proves to be efficient and improves filter performance. The efficiency of digital filter application can be improved by taking account of the features of their impulse response.
... So in the "window function" settings we used the setting of "Hamming" or close to this the "Cosine-Bell" setting. In these settings the level of suppression of side lobes is >40 dB (Goldenberg et al., 1985). This method ensures that stronger lateral petals do not mask the possible shortcomings of the spectral components. ...
... So "Hamming" function changes the amplitude to -5.5 dB compared to the original signal (Goldenberg et al., 1985), which corresponds to a decrease in the amplitude of about 53%. The last parameter that can significantly affect the results of spectral analysis is the degree of overlap of the FFT blocks. ...
... A presença de ruídos pode ser minimizada se é feito o pré-processamento dos dados coletados. Existem vários tipos de filtros que podem ser utilizados com essa finalidade, em especial o filtro de Kalman (CHAU et al., 2004;KAY, 1998;WILLIAMS;MADISETTI, 1997;OTTO, 2005;VANDEGINSTE et al., 1998). O filtro de Kalman apareceu em 1960, quando Rudolf Emil Kalman publicou um importante artigo descrevendo a solução recursiva para problemas lineares relacionados à filtragem de dados discretos (KALMAN et al., 1960). ...
... A presença de ruídos pode ser minimizada se é feito o pré-processamento dos dados coletados. Existem vários tipos de filtros que podem ser utilizados com essa finalidade, em especial o filtro de Kalman (CHAU et al., 2004;KAY, 1998;WILLIAMS;MADISETTI, 1997;OTTO, 2005;VANDEGINSTE et al., 1998). O filtro de Kalman apareceu em 1960, quando Rudolf Emil Kalman publicou um importante artigo descrevendo a solução recursiva para problemas lineares relacionados à filtragem de dados discretos (KALMAN et al., 1960). ...
... A number of audio compression techniques are in common usage. MPEG standards [1] contain several techniques and algorithms for the compression of audio signals, as do some proprietary coders such as the Dolby AC series of coders [2]. The techniques presented by those standards and products are aimed at non-scalable transmission rates; that is, most of the techniques standardized are defined for a given bit rate. ...
... An iterative procedure is employed where bits are assigned according to some distortion criteria [11]. This technique is used in the MPEG and Dolby AC transform coders [1] [2]. Another way of using the masking curves is to ignore all spectral components below the curve. ...
This paper presents an audio coder based on the combination of the Modulated Lapped Transform (MLT) with the Set Par- titioning In Hierarchical Trees (SPIHT) algorithm. SPIHT al- lows scalable coding by transmitting more important informa- tion first in an efficient manner. The results presented reveal that the Modulated Lapped Transform (MLT) based scheme produces a high compression ratio for little or no loss of quality. A modification is introduced to SPIHT which further improves the performance of the algorithm when it is being used with uniform M-band transforms and masking. Further, the MLT- SPIHT scheme is shown to achieve high quality synthesized audio at 54 kbps through subjective listening tests.
... The amplitude at specific frequencies in the frequency-domain signal can help in detecting anomalies, that is faults. Although FFT analysis is significantly used for fault monitoring and diagnostic in IMs, the algorithm suffers from problems which include overlapping of closely located spectral components, sensitivity to low signal-to-noise ratio, spectral leakage that affects its efficiency [6]. ...
Early fault detection in an induction motor is the need of modern industries for minimal downtime and maximum production. A learning technique known as the Convolutional Neural network (CNN) provides automated and reliable feature extraction and selection. Considering these inherent traits of CNN, this study proposes a CNN in combination with batch normalisation (BN)‐based fault detection approach for simultaneous detection of bearing fault and broken rotor bars in squirrel cage induction motors (SCIMs). The SCIM vibration signals have different patterns for different defects, and the architecture of CNN is used in this study for fault diagnosis. For an efficient fault feature extraction, the proposed method uses CNN having multiple stacked layers with BN for faster training. In the proposed method, a CNN model with small kernel size is used along with adaptive gradient optimizer and BN to avoid performance degradation and optimum results. For the validation of the proposed technique, a test set‐up is used along with different fault conditions. The proposed method is also compared with the existing state‐of‐the‐art methods to illustrate its effectiveness.
... where s τ (t) is the auto-correlation of r(t). As widely known the auto-correlation function is periodic with T 0 for secondorder cyclostationary signals [37]. Therefore, it can be expanded to Fourier series coefficients as ...
Radio air interface identification provides necessary information for dynamically and efficiently exploiting the wireless radio frequency spectrum. In this study, a general machine learning framework is proposed for Global System for Mobile communications (GSM), Wideband Code Division Multiple Access (WCDMA), and Long Term Evolution (LTE) signal identification by utilizing the outputs of the spectral correlation function (SCF), fast Fourier Transform (FFT), auto–correlation function (ACF), and power spectral density (PSD) as the training inputs for the support vector machines (SVMs). In order to show the robustness and practicality of the proposed method, the performance of the classifier is investigated with respect to different fading channels by using simulation data. Various over–the–air real–world measurements are taken to show that wireless signals can be successfully distinguished from each other without any prior information while accounting for a comprehensive set of parameters such as different kernel types, number of in–phase/quadrature (I/Q) samples, training set size, or signal–to–noise ratio (SNR) values. Furthermore, the performance of the proposed classifier is compared to the existing well–known deep learning (DL) networks. The comparative performance of the proposed method is also quantified by classification confusion matrices and Precision/Recall/F1–scores. It is shown that the investigated system can be also utilized for spectrum sensing and its performance is also compared with that of cyclostationary feature detection spectrum sensing.
... The basis theory of SC is cyclostationarity which has been existing for several decades [11,12]. A random signal can be defined as stationary at th order if its time-domain th-order moment will not vary according to the time , and a random signal can be defined as having the characteristic of cyclostationarity at th-order if the period of its time domain th-order moment is a periodical function of time . ...
When fault arises in the rolling element bearing, the time-domain waveform of fault vibration signal will take on the characteristic of cyclostationarity, and the spectral correlation (SC) or spectral correlation density (SCD) basing on second order cyclic statistic is an effective cyclostationarity signal processing method. However, when the fault signal is surrounded by strong background noise, the traditional signal processing methods such envelope demodulation analysis and SC would not work effectively. The paper improves the SC method and a new time-frequency analysis method naming improved spectral correlation (ISC) is proposed. The proposed method is much more noise-resistant than SC through the verification of simulation analysis results. Besides, it takes on modulation phenomenon usually when fault arises in the rolling element bearing and the aim of fault feature extraction is to extract the fault characteristic frequency only or cyclic modulation frequency and the modulated frequency or carrier frequency buried in the object vibration signal is neglected. So, the paper improves the ISC further and the improved ISC (IISC) is proposed. The IISC will extract the modulation frequency only and it has the advantages of much clearer expression effect and better extraction effect. The effectiveness and feasibility of the proposed method are verified through the three kinds of fault (inner race fault, outer race fault and rolling element fault) of rolling element bearing. Besides, the advantages of the proposed method over the other relative time-frequency analysis methods such as ensemble empirical mode decomposition (EEMD) and spectral kurtosis (SK) are also presented in the paper.
... The cyclostationary process, sometimes called periodically stationary process, is special cases of non-stationary processes in the sense that their statistical properties are variants in the time but in a periodic way. Random nature information messages are combined with periodicity introduced by modulation, coding, etc. to gain the cyclostationarity [19][20]. ...
This work looks at the issue of the radiofrequency RF spectrum sensing for the detection of presence of the primary units PU within a licensed spectrum, in the context of the Cognitive Radio CR. The objective of this work is to develop a based-cyclostationary detection algorithm for detection of occupied RF spectral band otherwise a secondary user SU can allocate that RF bandwidth. We implement cyclostationary detection at the base of the cyclic autocorrelation function CAF upon the integrated development environment GNU Radio. The developed system is able to detect the presence of the UP, representing a message, carried by the AM modulation, transmitted on a RF AWGN channel, at a very low ratio to noise ratio SNR, up to-20 dB with a minimum of prior information and minimum complexity. The developed algorithm defines the carrier frequency, of the AM modulation, as well as the fundamental frequency of the transmitted message in appearance of dominant peaks, located at the frequency in question through the GUI and localization tools provided by the GNU Radio IDE.
... Two main representations are used to analyze the cyclostationary signals as described in [8] and [9]: Decimated Components and Subband Components. In the Decimated Components representation, the cyclostationary process x[n] with a period P is represented as P different stationary processes H0(ω) . ...
In this paper, we propose a cyclostationary noise model for multi-input multi-output (MIMO) narrowband power line communication (NB-PLC) based on frequency-shift (FRESH) filtering. The MIMO FRESH filters are designed to shape a multi-input white noise spectrum to a muti-output cyclic spectrum extracted from experimental noise measurements of three-phase low-voltage power lines. The noise modeling problem is formulated as a system identification problem that minimizes the time-averaged mean square error (TA-MSE) between a reference measured noise waveform and the model-generated noise waveform. We propose the normalized mean-square-error (NMSE) for both the cyclic auto-correlation and cyclic cross-correlation between the measured and the generated noise waveforms as a performance measure. The noise waveform generated by the proposed model shows a good agreement with that of the measured noise in terms of the cyclic auto/cross-correlation NMSE. Moreover, the proposed model provides a scalable performance-complexity tradeoff.
... Two main representations are used to analyze the cyclostationary signals as described in [8] and [9]: Decimated Components and Subband Components. In the Decimated Components representation, the cyclostationary process x[n] with a period P is represented as P different stationary processes H0(ω) . ...
... Two main representations are used to analyze the cyclostationary signals as described in [8] and [9]: Decimated Components and Subband Components. In the Decimated Components representation, the cyclostationary process x[n] with a period P is represented as P different stationary processes H0(ω) . ...
In this paper, we introduce a cyclostationary noise model for the narrowband powerline communication (NB-PLC) based on frequency-shift (FRESH) filters that are fitted to experimental noise measurements. In particular, the FRESH filter is designed to shape an input white noise spectrum to a cyclic spectrum extracted from experimental noise measurements. The proposed model enjoys scalable performance-complexity tradeoff. In addition, the noise waveform generated by this model shows good agreement with that of actually measured noise in terms of the cyclic power spectral density (PSD) even at a low computational complexity implementation. Moreover, the proposed model provides a more accurate cyclic PSD to that of the actual noise measurements over the narrowband powerline noise models presented in the literature.
... Approximately 150 trials of buttonpress were carried out, which can be enough to select around 120 epochs of artefact-free trials. The Welch periodogram (Hamming window of size 4 s, overlapping of 50%) was used to analyze the power spectrum from the EEG signals measured on FP1-O1 electrodes [26]. The event-related desynchronization/ event-related synchronization (ERD/ERS) patterns were computed on the EEG signals measured from the C3-FZ and C4-FZ electrodes during the motor tasks [22]. ...
An active orthosis (AO) is a robotic device that assists both human gait and rehabilitation therapy. This work proposes portable AOs, one for the knee joint and another for the ankle joint. Both AOs will be used to complete a robotic system that improves gait rehabilitation. The requirements for actuator selection, the biomechanical considerations during the AO design, the fi nite element method, and a control approach based on electroencephalographic and surface electromyographic signals are reviewed. This work contributes to the design of AOs for users with foot drop and knee fl exion impairment.
However, the potential of the proposed AOs to be part of a robotic gait rehabilitation system that improves the quality of life of stroke survivors requires further investigation.
... Approximately 150 trials of buttonpress were carried out, which can be enough to select around 120 epochs of artefact-free trials. The Welch periodogram (Hamming window of size 4 s, overlapping of 50%) was used to analyze the power spectrum from the EEG signals measured on FP1-O1 electrodes [26]. The event-related desynchronization/ event-related synchronization (ERD/ERS) patterns were computed on the EEG signals measured from the C3-FZ and C4-FZ electrodes during the motor tasks [22]. ...
An active orthosis (AO) is a robotic device that assists both human gait and rehabilitation therapy. This work proposes portable AOs, one for the knee joint and another for the ankle joint. Both AOs will be used to complete a robotic system that improves gait rehabilitation. The requirements for actuator selection, the biomechanical considerations during the AO design, the finite element method, and a control approach based on electroencephalographic and surface electromyographic signals are reviewed. This work contributes to the design of AOs for users with foot drop and knee flexion impairment. However, the potential of the proposed AOs to be part of a robotic gait rehabilitation system that improves the quality of life of stroke survivors requires further investigation.
... Approximately 150 trials of buttonpress were carried out, which can be enough to select around 120 epochs of artefact-free trials. The Welch periodogram (Hamming window of size 4 s, overlapping of 50%) was used to analyze the power spectrum from the EEG signals measured on FP1-O1 electrodes [26]. The event-related desynchronization/ event-related synchronization (ERD/ERS) patterns were computed on the EEG signals measured from the C3-FZ and C4-FZ electrodes during the motor tasks [22]. ...
An active orthosis (AO) is a robotic device that assists both human gait and rehabilitation therapy. This work proposes portable AOs, one for the knee joint and another for the ankle joint. Both AOs will be used to complete a robotic system that improves gait rehabilitation. The requirements for actuator selection, the biomechanical considerations during the AO design, the finite element method, and a control approach based on electroencephalographic and surface electromyographic signals are reviewed. This work contributes to the design of AOs for users with foot drop and knee flexion impairment. However, the potential of the proposed AOs to be part of a robotic gait rehabilitation system that improves the quality of life of stroke survivors requires further investigation.
... A number of audio compression techniques are well known. MPEG standards [1] present several techniques of compressing audio signals, as do some commercial coders such as the Dolby AC series of coders [2]. The techniques presented by those standards and products are aimed at constant rate transmission, although MPEG has made some attempts at standardising scalable compression techniques [1] [3]. ...
This paper discusses the application of the Set Par- titioning In Hierarchical Trees (SPIHT) algorithm to the compression of audio signals. Simultaneous masking is used to reduce the number of coefficients required for the representation of the audio signal. The proposed scheme is based on the combina- tion of the Modulated Lapped Transform (MLT) and SPIHT. Comparisons are also made with the Discrete Wavelet Transform (DWT) based scheme. Results presented reveal the compression achieved as well as the scalability of the proposed coding scheme. The MLT based scheme is shown to have compres- sion performance that is superior to the DWT based scheme.
... Morphologicaloperators are indices that are sensitive to the geometric characteristics of the signals and they are ar esult of morphological signal processing (Maragos 1998). The fundamental concept of morphological signal processing is the modification of the shape of the signal through its interaction with another object, called the structuring element. ...
Frequency domain based signal processing methods have been shown to present a quite effective behaviour in the detection of defects, when applied to the analysis of vibration signals, resulting from rolling element bearings. However, these methods typically require some complex and sophisticated analysis, which renders their application cumbersome for applications requiring unskilled personnel or automated fault detection and trending. Parallel, a number of traditional methods exist, such as the root mean square (RMS), the crest factor (CF), the kurtosis (KU), the impulse factor (IF) and the shape factor (SF), requiring only direct processing in the time domain. Alternatively to these methods, a morphological index (MI) for processing vibration signals has been proposed, addressing the issues of how to quantify the shape and the size of the signals directly in the time domain. In this paper, based on a model for the dynamic behaviour of defective rolling bearings, the sensitivity of the MI is assessed, compared to the previous five traditional time domain indices, with respect to the effect of the added noise, the impulse repetition period, as well as the natural period and the damping ratio of the excited resonance, both in the case of an inner and an outer race defect. The results clearly indicate the superiority of the MI over all the other time domain indices compared. This fact is then further verified in three different cases from industrial installations, presenting fault trending analysis of bearings under various defects.
... Morphological signal processing comprises a broad collection of theoretical concepts and mathematical tools for signal analysis, nonlinear signal operators, design methodologies and application systems that are related to mathematical morphology (MM) [15, 16]. Morphological signal processing was first used to analyze binary image data and then extended to gray-level images [17]. ...
This paper presents a novel pattern classification approach for the fault diagnostics of rolling element bearings, which combines the morphological multi-scale analysis and the 'one to others' support vector machine (SVM) classifiers. The morphological pattern spectrum describes the shape characteristics of the inspected signal based on the morphological opening operation with multi-scale structuring elements. The pattern spectrum entropy and the barycenter scale location of the spectrum curve are extracted as the feature vectors presenting different faults of the bearing, which are more effective and representative than the kurtosis and the enveloping demodulation spectrum. The 'one to others' SVM algorithm is adopted to distinguish six kinds of fault signals which were measured in the experimental test rig under eight different working conditions. The recognition results of the SVM are ideal and more precise than those of the artificial neural network even though the training samples are few. The combination of the morphological pattern spectrum parameters and the 'one to others' multi-class SVM algorithm is suitable for the on-line automated fault diagnosis of the rolling element bearings. This application is promising and worth well exploiting.
... This paper considers as a possible alternative, the application of a purely time domain analysis procedure, based on morphological wavelet (MW) decomposition concepts. Morphological signal processing comprises a broad collection of theoretical concepts and mathematical tools for signal analysis, nonlinear signal operators, design methodologies and application systems that are related to mathematical morphology (MM) [5,6]. Morphological signal processing was firstly used to analyze binary image data and was then extended to gray-level images [7]. ...
This paper presents a novel morphological undecimated wavelet (MUDW) decomposition scheme for fault diagnostics of rolling element bearings. The MUDW scheme is developed based on the morphological wavelet (MW) theory for both the extraction of impulse features and noise smoothing in signal processing. The analysis operators and the synthesis operator of MUDW strictly satisfy the pyramid condition. The MUDW scheme is used to extract impulse features from rolling element bearing defect signals imposed with noise. The efficiency of the MUDW scheme used for noise smoothing and the extraction of impulse components is evaluated using the simulated data and measured signals from the bearing test rig. Compared with enveloping demodulation analysis, the MW transform and the traditional wavelet transform (WT), the MUDW decomposition scheme is more effective and suitable for the on-line diagnostics of bearings in rotating machines.
... The first step is the image pre-smoothing with a non-linear morphological filter, a so-called ASF (Alternating Sequential Filter). This filter is based on morphological area opening (@BULLET) and closing (@BULLET) operations with structure elements of increasing scale [15]. More specifically, if S i , i=1,...,4, is the 2-pixel connected line segments oriented at 90(i-1) degrees, and nS i is the corresponding (n+1)-pixel elements of size n = 1, 2, 3, ...., then the openings α n and closings β n that make up the filter, for an image I, are, Then the filtered image I ASF is obtained by the following cascade, ...
Tracking moving objects in video sequences is a task that emerges in various fields of study: video analysis, computer vision, biomedical systems, etc. In the last decade, special attention has been drawn to problems concerning tracking in real-world environments, where moving objects do not obey any afore-known constraints about their nature and motion or the scenes they are moving in. Apart from the existence of noise and environmental changes, many problems are also concerned, due to background texture, complicated object motion, and deformable and/or articulated objects, changing their shape while moving along time. Another phenomenon in natural sequences is the appearance of occlusions between different objects, whose handling requires motion information and, in some cases, additional constraints. In this work, we revisit one of the most known active contours, the Snakes, and we propose a motion-based utilization of it, aiming at successful handling of the previously mentioned problems. The use of the object motion history and first order statistical measurements of it, provide us with information for the extraction of uncertainty regions, a kind of shape prior knowledge w.r.t. the allowed object deformations. This constraining also makes the proposed method efficient, handling the trade-off between accuracy and computation complexity. The energy minimization is approximated by a force-based approach inside the extracted uncertainty regions, and the weights of the total snake energy function are automatically estimated as respective weights in the resulting evolution force. Finally, in order to handle background complexity and partial occlusion cases, we introduce two rules, according to which the moving object region is correctly separated from the background, whereas the occluded boundaries are estimated according to the object's expected shape. To verify the performance of the proposed method, some experimental results are included, concerning different cases of object tracking, indoors and outdoors, with rigid and deformable objects, noisy and textured backgrounds, as well as appearance of occlusions.
Frequency modulation (FM) is widely used in telemetry systems, as well as in telephone, radio relay and satellite communication systems. The use of FM significantly improves the use of transmitter power and increases the noise immunity of reception.
In the radio frequency range, a large number of radio systems for various purposes operate simultaneously, the transmitting devices of which, along with various high-frequency installations (industrial, scientific, medical, household and other purposes), are sources of unintentional electromagnetic interference.
A three-dimensional antenna array with a spherical surface was investigated. The channels were randomly placed at array points with a vertical and horizontal step equal to 0.45 wavelengths. For uniform filling of the sphere, the minimum allowable distance between the channels was introduced, depending on the number of channels and the sphere size. The maximum side lobe level depends on the number of channels. To calculate the path difference in a given direction, the coordinate system was rotated so that one of the coordinate axes coincided with the selected direction. To find the radiation pattern, the scalar product of the amplitude-phase distribution vector corresponding to the signal emission direction was calculated by the complex-conjugate vector of the amplitude-phase distribution corresponding to all possible directions of signal arrival from an external source.
The transient electromagnetic method (TEM) survey was carried out within one of the private house area to allocate the fresh water reservoirs in Greece.
There are two challenges that make the problem complex. The first is noisy settings for geophysical survey: populated area with power lines, pipes, houses etc. The second challenge is uncertainties with water-bearing reservoirs.
According to geological settings and water-bearing reservoirs location, geophysical survey had to maintain penetration depth up to 250-300 m. For this task DC (direct current) methods are not applicable whereas induction electromagnetic sounding like Transient electromagnetic method (TEM) in the near field zone can show superior results. Therefore TEM survey was carried out.
To ensure the high quality of TEM data the special algorithms of electromagnetic noise attenuation were applied.
From TEM results it was found, that at a depth of about 180–280 m in the southeastern part of the study area, one can expect the presence of fresh water, and the resistance values are 80 Ω·m.
Due to the formal approach to the task of interpolation in the digital signal processing (DSP) statement, existing software implementations of methods for the discrete-time signals (DST) sample rate increase might work incorrectly. In the paper, we have researched features of the method for generation of the DTS with the sample rate increased by integer number of times. We have analyzed results of the DTS reconstruction by means of the MATLAB function interp.m. We have shown that the DTS with an increased sample rate might not satisfy the interpolation task requirements, thus, may vary comparing to results of the DTS reconstruction by means of other classic interpolation methods.
At present, the receivers, in which the received analog radio signal is converted into the digital form after preliminary processing, are most widely distributed to execute radio monitoring. © 2018, Springer International Publishing AG, part of Springer Nature.
We show that hardware implementation of digital filters is accompanied by the problem connected with using a finite number of bits for representing coefficients, input data and interim results. This problem leads to the deterioration of magnitude response and computation accuracy. We provide grounds for using modular coding in digital filters in order to exclude errors caused by finite capacity when computing output samples. Thus, it becomes possible to meet the requirements to computational accuracy and magnitude response without increasing hardware costs and computation time.
Numerical investigation of mixing non-isothermal streams of sodium coolant in a T-branch is carried out in the FlowVision CFD software. This study is aimed at argumentation of applicability of different approaches to prediction of oscillating behavior of the flow in the mixing zone and simulation of temperature pulsations. The following approaches are considered: URANS (Unsteady Reynolds Averaged Navier Stokers), LES (Large Eddy Simulation) and quasi-DNS (Direct Numerical Simulation). One of the main tasks of the work is detection of the advantages and drawbacks of the aforementioned approaches.
Numerical investigation of temperature pulsations, arising in the liquid and T-branch walls from the mixing of non-isothermal streams of sodium coolant was carried out within a mathematical model assuming that the flow is turbulent, the fluid density does not depend on pressure, and that heat exchange proceeds between the coolant and T-branch walls. Model LMS designed for modeling turbulent heat transfer was used in the calculations within URANS approach. The model allows calculation of the Prandtl number distribution over the computational domain.
Preliminary study was dedicated to estimation of the influence of computational grid on the development of oscillating flow and character of temperature pulsation within the aforementioned approaches. The study resulted in formulation of criteria for grid generation for each approach.
Then, calculations of three flow regimes have been carried out. The regimes differ by the ratios of the sodium mass flow rates and temperatures at the T-branch inlets. Each regime was calculated with use of the URANS, LES and quasi-DNS approaches.
At the final stage of the work analytical comparison of numerical and experimental data was performed. Advantages and drawbacks of each approach to simulation of mixing non-isothermal streams of sodium coolant in the T-branch are revealed and formulated.
It is shown that the URANS approach predicts the mean temperature distribution with a reasonable accuracy. It requires essentially less computational and time resources compared to the LES and DNS approaches. The drawback of this approach is that it does not reproduce pulsations of velocity, pressure and temperature.
The LES and DNS approaches also predict the mean temperature with a reasonable accuracy. They provide oscillating solutions. The obtained amplitudes of the temperature pulsations exceed the experimental ones. The spectral power densities in the check points inside the sodium flow agree well with the experimental data. However, the expenses of the computational and time resources essentially exceed those for the URANS approach in the performed numerical experiments: 350 times for LES and 1500 times for ·DNS.
This paper describes how a mechanical disturbance on the shaft of a variable speed permanent magnet motor (PMSM) is propagated to the supply input side of the drive system, and therefore may be detected by monitoring specific frequency components in the rectifier input current. The propagation of the disturbance from the torque disturbance, to the motor current, then to the dc link current and finally to the rectifier input current is derived as a series of transfer functions so that both the frequency and the amplitude of the disturbance component in the rectifier input current can be predicted for a specific mechanical disturbance. The limitations to detect the mechanical fault by monitoring only the supply currents are also addressed. Simulation and experimental results are presented to demonstrate the accuracy of the quantitative analysis, and the potential for fault detection using the rectifier input currents.
This paper describes the project of an accumulative cell of a silicon integrated signal reading circuit with a built-in analog-digital converter for matrix IR photodetectors based on the Hg1-xCdxTe solid solutions with the sensitivity in the spectral range from 8 to 10 µm. The cell is designed according to the silicon technology HCMOS8D of JSC “NIIME i Mikron” (Moscow) with a project norm of 0.18 µm. The presented project of the cell has the size of 20×2020 µm, and the number of bits in the built-in analog-digital converter is 15. When the average photocurrent is 7 nA and the integration time is 7.5 ms, the estimated value of the noise equivalent delta temperature is 4.6 mK.
Moving object detection and tracking in video sequences is a task that emerges in various research fields of video processing, including video analysis and understanding, object-based coding and many related applications, such as content-based retrieval, remote surveillance and object recognition. This work revisits one of the most popular deformable templates for shape modeling and object tracking, the Snakes, and proposes a modified snake model and a probabilistic utilization of it for object tracking. Special attention has been drawn to complex natural (indoor and outdoor) sequences, where temporal clutter, abrupt motion and external lighting changes are crucial for the accuracy of the results, also focusing on the ability of the proposed approach to handle specific HCI problems, such as face and facial feature tracking. A variety of image sequences are used to illustrate the method's capability, providing theoretical explanation as well as experimental verification in specific tracking problems.
Color fringe is an artifact that should be removed in a color digital image. This paper proposes a detection method of color fringe in narrow color regions. Near-saturation region (NSR) information as well as gradient magnitudes and directions of RGB color components are used to detect transition regions, in which color fringe occurs. Four gradient directions are used in order to improve the performance of color fringe detection. NSR is used to prevent excessive detection of possible color fringe regions. Then, the detected color fringe is removed using the color difference values. Experimental results show the effectiveness of the proposed color fringe removal method.
A method to estimate the line of sight(LOS) rate of strapdown imaging seeker based on Particle Filter(PF) is presented. PF algorithm is firstly put forward and then the model of strapdown imaging seeker is introduced. Because of the high nonlinearity in both process and measurement equations and more seriously nonGaussian noise in the measurements, the normally used Extended Kalman Filter(EKF) can not completely meet the requirements of filtering. Comparatively, PF is a congruent method for tracking in the conditions of nonlinearity and nonGaussian noise. At the last, PF and EKF are applied to estimate the LOS rate of strapdown imaging seeker respectively. Simulation results show that PF is more precise than EKF in LOS rate estimation.
The fault diagnostics and identification of rolling element bearings have been the subject of extensive research. This paper presents a novel pattern classification approach for the fault diagnostics, which combines the morphological multi-scale analysis and the ¿one to others¿ support vector machine (SVM) classifiers. Morphological pattern spectrum describes the shape characteristics of the inspected signal based on the morphological opening operation with multi-scale structuring elements. The pattern spectrum entropy and the barycenter scale location of the spectrum curve are extracted as the feature vectors presenting different faults of the bearings. The ¿one to others¿ SVM algorithm is adopted to distinguish six kinds of fault bearing signals which were measured in the experimental test rig running under eight different working conditions. The recognition results of the SVM are ideal even though the training sample is few. The combination of the morphological pattern spectrum parameter analysis and the ¿one to others¿ multi-class SVM algorithm is suitable for the on-line automated fault diagnosis of the rolling element bearings. This application is promising and worth well exploiting.
In passive coherent radar tracking using external illuminator as transmitters, the traditional extended Kalman filter (EKF) is adopted frequently, but the tracking performance is affected seriously by the glint noise in practice. To solve this problem, a novel passive coherent radar tracking method is proposed based on particle filter (PF) and only time difference of arrival (TDOA) measurements. This new approach obtain measurements from multiple TDOA locating model, and then by using particle filter to track target, which avoid the error caused by EKF linearization, and reduce the measurements error resulted from glint noise, so it can improve the tracking precision. The simulation results show that the performance of the proposed method is superior to that of the EKF algorithm not only in Gaussian but also in glint noise environment. The experiment based on real data demonstrates the validity and feasibility of the new method.
The defects diagnosis and pattern classification are presented in this paper. Morphological pattern spectrum describes the shape characteristics of the inspected signal based on the morphological opening operation with multi-scale structuring elements. The pattern spectrum entropy and the barycenter scale location of the spectrum curve are extracted as the feature vector presenting different defects of the rolling bearings. The support vector machinery (SVM) algorithm is adopted to distinguish different kinds of defective bearing signals. The recognition results of the SVM are ideal and more precise than that of the artificial neural network. The combination of the morphological pattern spectrum parameter analysis and the SVM algorithm is suitable for the on-line automated defect diagnosis of the rolling bearing.
The vibration signal from a faulty rolling element bearing is not strictly phase locked to the rotational speed of the shaft,
due to the variable slip between the bearing elements. For this reason, the classical diagnostic methods, which are based
on Fourier analysis, cannot detect clearly the modulation phenomena and the type of the defect, because the relevant information
contained in the second order statistic measures is diminished. The main purpose of this paper is the combination of cyclostationary
and higher order statistic analysis methods, which can lead to better results, concerning the identification of the status
of the bearing. The paper demonstrates that the cyclic bispectral analysis can lead to a discrete spectral structure, enabling
the clear detection the type of the bearing fault and the corresponding modulation mechanism, thus significantly overcoming
the corresponding problem of other existing methods.
Das Fehlersignal eines Lagers ist wegen der variablen Versetzung zwischen den Lagerteilen nicht mit seiner Drehgeschwindigkeit
in Phase. Daraus folgt, dass die klassische, auf der Fourier-Analyse basierenden Diagnostikmethode nicht in der Lage ist,
das Modulationsphänomen und den Defektstyp eindeutig zu detektieren. Das Hauptziel dieser Arbeit ist die Kombination der zyklostationären
Analyse mit einer Statistik höheren Grades, was zu interessanten Ergebnissen, im Bezug auf den Lagerzustand, führt. Die Studie
beweist, dass die zyklische bispektrale Analyse in der Lage ist eine diskrete Struktur zu finden, die den Fehlertyp und den
Modulationsmechanismus detektiert, nach dem sie die Probleme der anderen Methoden infolge der Versetzung überwindet.
Systems of LFM radar signals coherent packet processing with pulsed noise (PN) censoring at the input of matched filter (MF) and frequency threshold (FT), provided low level of false alarm probability from signals, reflected from point moving clutter (PMC), are considered. Characteristics of moving target signals detection are obtained and values of false alarm rate from PMC in conditions of simultaneously influencing PN are determined.
It is known that digital image restoration is an ill-conditioned
problem in the sense that small deviations like noise in the degraded
image produce large deviations in the estimation of the original image.
On the other hand, perturbations in the point spread function of the
system also result in poor quality restorations. Since the knowledge of
the point spread function generally is not exact, the robustness of a
restoration method with respect to variations of the point spread
function is an important feature to take into account. The paper has the
goal of analysing this robustness for some iterative restoration methods
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