Kristina Lukoseviciute

Kaunas University of Technology · Department of Applied Mathematics

The internal smoothing approach for Chebyshev interpolation is used in this paper. Due to the properties of the Chebyshev interpolation the proposed technique is only applicable to a very short-term prediction of a given time series. One step ahead prediction is performed in this paper. The results are compared to a number of other time series pred...

We introduce a short-term time series prediction model by means of evolutionary algorithms and Bernstein polynomials. This adapts Bernstein-type algebraic skeletons to extrapolate and predict short time series. A mixed smoothing strategy is used to achieve the necessary balance between the roughness of the algebraic prediction and the smoothness of...

Short time series prediction technique based on Bernstein polynomials is presented in this paper. Firstly, the straightforward Bernstein polynomial extrapolation scheme is improved by extending the interval of approximation. Secondly, the forecasting scheme is designed in the evolutionary computational setup which is based on the conciliation betwe...

ToF estimation errors for two reflections have been analyzed. Case of high signal-to-noise ratio was assumed, when accuracy of the order of few nanoseconds can be achieved. It was indicated that additional bias errors are introduced in ToF estimator when other reflection is in close temporal proximity to the reflection of interest. Research demonst...

Iterative polynomial model for synchronization of vibrations was proposed. A polynomial was constructed using time delay coordinates. For time delay kernel estimation, a non-uniform embedding was used. Evolutionary optimization algorithms were introduced for non-uniform time delay identification. Performance investigation of proposed method was don...

Comparison of the approximation performance of the ultrasonic reflections by simple model functions used in blind deconvolution is presented. New model function was proposed where causality of the signal is easily modelled without the need for piecewise-linear equations. Parameter estimation technique was developed. Performance investigation was do...

Case is when two reflections are in close proximity is analysed. Such proximity introduces bias errors in ToF estimators for all interfering signals. Purpose of the investigation was the comparison of the time and frequency domain estimation algorithms with the aim to establish the insight into possible algorithms which are capable to reduce those...

Optimal selection of time delay for time series reconstruction is an important problem in time series analysis and forecasting. When reconstructing the time series into phase space with non-uniform time delay, a time delay selection becomes a difficult optimization problem. To solve this problem, this paper presents two optimization algorithms: cuc...

An algebraic segmentation method based on algebraic predictor with internal smoothing is proposed. The concept of the rank of the sequence is proposed for the detection of a base fragment of the sequence. Numerical experiments with a real-world financial time series illustrate the segmentation method.

Resolution of ultrasonic imaging demands wideband signals for excitation. If bandwidth improvement is done by reduction of the pulse duration signal to noise ratio is reduced. Spread spectrum signals allow increasing the signal energy and maintaining the resolution. Since signal frequency components are spread in time resolution is not reduced: suc...

Resolution and signal-to-noise ratio performance improvement of ultrasound applications in measurement or imaging demands both high energy and wideband signals for excitation. Conventional signals like pulse and toneburst do not satisfy both requirements, but spread spectrum signals are capable to increase the signal energy and maintain the resolut...

Adaptive algebraic level-set segmentation algorithm of financial time series is presented in this paper. The proposed algorithm is based on the algebraic one step-forward predictor with internal smoothing, which is used to identify a near optimal algebraic model. Particle swarm optimization algorithm is exploited for the detection of a base algebra...

Performance comparison of conventional and spread spectrum signals in Time of Flight estimation is given. Ultrasonic measurement under multiple reflections condition is analyzed. It was indicated that if two reflections are in close proximity the neighboring signal induces energy leak into its opponent signal. Due to such situation ToF estimate is...

This work presents an investigation of the bias error introduced in time of flight estimation realized by subsample interpolation in digital domain. The time of flight estimation is accomplished based on the evaluation of the peak position of the cross correlation function. In order to cope with the discrete nature of the cross-correlation function...

Investigation of the errors of Time of Flight (ToF) estimate of ultrasonic signals in case of multiple reflections environment is presented. Multiple signals environment induces neighboring signal energy leak into analyzed signal. This in turn introduces some errors in ToF estimate. Narrow signals like single pulse, should posses lower influence th...

Resolution and signal-to-noise ratio performance improvement of ultrasound applications in measurement or imaging demands both high energy and wideband signals for excitation. Conventional signals, like pulse and continuous waves (CW) burst do not satisfy both requirements. But spread spectrum signals are capable to increase the signal energy and m...

Ultrasonic imaging requires both the accuracy and the resolution. Conventional imaging systems use the pulse signals to accomplish the task. But the energy attainable with such signals is limited. Spread spectrum, compressible signals allow to achieve the wide bandwidth even using long durations. Conventional signals do not offer full flexibility o...

Time series forecasting by fuzzy inference systems based on optimal non-uniform attractor embedding in the multidimensional delay phase space is analyzed in this paper. A near-optimal set of time lags is identified by evolutionary algorithms after the optimal dimension of the reconstructed phase space is determined by the FNN (false nearest neighbo...

A new method for identification of an optimal set of time lags based on non-uniform attractor embedding from the observed non-linear time series is proposed in this paper. Simple deterministic method for the determination of non-uniform time lags comprises the pre-processing stage of the time series forecasting algorithm which is implemented in the...

A new method for time series forecasting by fuzzy inference systems based on non-uniform attractor embedding and genetic algorithms is proposed in this paper. A near optimal set of time lags is identified by genetic algorithms. The parameter characterizing the spreading of the embedded attractor in the delay coordinate space is used as a fitness fu...

An algorithm for the construction of cryptographic hash function based on optical time average geometric moiré, chaotic dynamics and digital image processing is proposed in this paper. This algorithm is based on the fact that inverse problem for identification of the original grayscale color function from its time averaged image is an ill-posed pro...

Inverse problems involving time average geometric moiré are characterized by the fact that the information of interest (the distribution of grayscale level on the static surface) is not directly available. The imaging device (the camera) provides measurements of a transformation of this information in the process of time averaging while the body pe...