Constantin Paleologu

Polytechnic University of Bucharest | UPB · Department of Telecommunications

This work focuses on linear system identification problems in the framework of the Wiener filter. Specifically, it addresses the challenging identification of systems characterized by impulse responses of long length, which poses significant difficulties due to the existence of large parameter space. The proposed solution targets a dimensionality r...

Signal, video and image processing constitutes the basis of communications systems. With the proliferation of portable/implantable devices, embedded signal processing became widely used, despite that most of the common users are not aware of this issue. New signal, image and video processing algorithms and methods, in the context of a growing-wide...

In the new era of digital revolution, the digital sensors and embedded designs become cheaper and more present [...]

Stereophonic audio devices employ two loudspeakers and two microphones in order to create a bidirectional sound effect. In this context, the stereophonic acoustic echo cancellation (SAEC) setup requires the estimation of four echo paths, each one corresponding to a loudspeaker-to-microphone pair. The widely linear (WL) model was proposed in recent...

A wide variety of system identification problems can be efficiently addressed based on the Kronecker product decomposition of the impulse response, together with low-rank approximations. Such an approach solves the original system identification problem using a combination of two shorter filters. In this paper, targeting a higher dimensionality red...

The identification of long-length impulse responses represents a challenge in the context of many applications, like echo cancellation. Recently, the problem has been addressed in the framework of low-rank systems, using a decomposition of the impulse response based on the nearest Kronecker product and low-rank approximations. As a result, the orig...

This paper presents a stochastic model for the least-mean-square algorithm with symmetric/antisymmetric properties (LMS-SAS), operating in a system identification setup with Gaussian input data. Specifically, model expressions are derived to describe the mean weight behavior of the (global and virtual) adaptive filters, learning curves, and evoluti...

In linear system identification problems, it is important to reveal and exploit any specific intrinsic characteristic of the impulse responses, in order to improve the overall performance, especially in terms of the accuracy and complexity of the solution. In this paper, we focus on the nearest Kronecker product decomposition of the impulse respons...

The principal issue in acoustic echo cancellation (AEC) is to estimate the impulse response between the loudspeaker and microphone of a hands-free communication device. This application can be addressed as a system identification problem, which can be solved by using an adaptive filter. The most common one for AEC is the normalized least-mean-squar...

Nonlinear systems have been studied for a long time and have applications in numerous research fields. However, there is currently no global solution for nonlinear system identification, and different used approaches depend on the type of nonlinearity. An interesting class of nonlinear systems, with a wide range of popular applications, is represen...

The multilinear system framework allows for the exploitation of the system identification problem from different perspectives in the context of various applications, such as nonlinear acoustic echo cancellation, multi-party audio conferencing, and video conferencing, in which the system could be modeled through parallel or cascaded filters. In this...

There are different strategies to improve the overall performance of the recursive least-squares (RLS) adaptive filter. In this letter, we focus on the data-reuse approach, aiming to improve the convergence rate/tracking of the algorithm by reusing the same set of data (i.e., the input and reference signals) several times. First, we present a compu...

The identification of room acoustic impulse responses represents a challenging problem in the framework of many important applications related to the acoustic environment, like echo cancellation, noise reduction, and microphone arrays, among others. The main issues are related to the long length of such impulse responses and their time-variant natu...

This paper presents a stochastic model of the least-mean-square for bilinear forms (LMS-BF) algorithm in which the bilinear term is defined with respect to the temporal and spatial impulse responses of a multiple-input/single-output (MISO) spatiotemporal system. Specifically, taking into account uncorrelated and correlated Gaussian input data, an a...

Efficiently solving a system identification problem represents an important step in numerous important applications. In this framework, some of the most popular solutions rely on the Wiener filter, which is widely used in practice. Moreover, it also represents a benchmark for other related optimization problems. In this paper, new insights into the...

System identification problems are always challenging to address in applications that involve long impulse responses, especially in the framework of multichannel systems. In this context, the main goal of this review paper is to promote some recent developments that exploit decomposition-based approaches to multiple-input/single-output (MISO) syste...

The Kalman filter represents a very popular signal processing tool, with a wide range of applications within many fields. Following a Bayesian framework, the Kalman filter recursively provides an optimal estimate of a set of unknown variables based on a set of noisy observations. Therefore, it fits system identification problems very well. Neverthe...

Tensor-based signal processing methods are usually employed when dealing with multidimensional data and/or systems with a large parameter space. In this paper, we present a family of tensor-based adaptive filtering algorithms, which are suitable for high-dimension system identification problems. The basic idea is to exploit a decomposition-based ap...

Solving the person re-identification problem involves making associations between the same person’s appearances across disjoint camera views. Further, those associations have to be made on multiple surveillance cameras in order to obtain a more efficient and powerful re-identification system. The re-identification problem becomes particularly chall...

High-dimensional system identification problems can be efficiently addressed based on tensor decompositions and modelling. In this paper, we design a recursive least-squares (RLS) algorithm tailored for the identification of trilinear forms, namely RLS-TF. In our framework, the trilinear form is related to the decomposition of a third-order tensor...

Adaptive algorithms with differential step-sizes (related to the filter coefficients) are wellknown in the literature, most frequently as “proportionate” algorithms. Usually, they are derivedon a heuristic basis. In this paper, we introduce an algorithm resulting from an optimization criterion.Thereby, we obtain a benchmark algorithm and also anoth...

Multi-User (MU) Multiple-Input-Multiple-Output (MIMO) systems have been extensively investigated over the last few years from both theoretical and practical perspectives. The low complexity Linear Precoding (LP) schemes for MU-MIMO are already deployed in Long-Term Evolution (LTE) networks; however, they do not work well for users with strongly-cor...

System identification problems are very difficult in the scenario of long length impulse responses, raising challenges in terms of convergence, complexity, and accuracy of the solution. However, we can take advantage of the characteristics of the impulse response, in order to improve the overall performance. In this context, a recently introduced a...

The least-mean-square (LMS) and the normalized least-mean-square (NLMS) algorithms require a trade-off between fast convergence and low misadjustment, obtained by choosing the control parameters. In general, time variable parameters are proposed according to different rules. Many studies on the optimization of the NLMS algorithm imply time variable...

The theory of nonlinear systems can currently be encountered in many important fields, while the nonlinear behavior of electronic systems and devices has been studied for a long time. However, a global approach for dealing with nonlinear systems does not exist and the methods to address this problem differ depending on the application and on the ty...

The recursive least-squares (RLS) adaptive filter is an appealing choice in many system identification problems. The main reason behind its popularity is its fast convergence rate. However, this algorithm is computationally very complex, which may make it useless for the identification of long length impulse responses, like in echo cancellation. Co...

The system identification problem becomes more challenging when the parameter space increases. Recently, several works have focused on the identification of bilinear forms, which are related to the impulse responses of a spatiotemporal model, in the context of a multiple-input/ single-output system. In this framework, the problem was addressed in t...

Due to its fast convergence rate, the recursive least-squares (RLS) algorithm is very popular in many applications of adaptive filtering, including system identification scenarios. However, the computational complexity of this algorithm represents a major limitation in applications that involve long filters. Moreover, when the parameter space becom...

In the modern era, audio or video recording is at everyone’s disposal any time with very low costs. Technology advances allow cameras and microphones to be installed in the most casual accessories like eyeglasses or clothes. Moreover, multimedia editing is also massively available. Near professional forgeries can be made using free software. Given...

With 3GPP 5G new radio (NR), proposals are already being discussed. Although participants offer various suggestions for the first 5G standardization, common ideas can already be identified. The purpose of the paper is to anticipate, in the context of massive multiple input multiple output (MIMO) systems, the main directions the standard would focus...

In order to improve the performance of the conventional algorithms used for network and acoustic echo cancellation, we can exploit the sparseness character of the echo paths (i.e., a small percentage of the impulse response components have a significant magnitude while the rest are zero or small). In this paper, we consider the memory-improved prop...

Linear system identification is a key problem in many important applications, among which echo cancellation is a very challenging one. Due to the long length impulse responses (i.e., echo paths) to be identified, there is always room (and needs) to improve the performance of the echo cancellers, especially in terms of complexity, convergence rate,...

Bilinear systems are involved in many interesting applications, especially related to the approximation of nonlinear systems. In this context, the bilinear term is usually defined in terms of an input–output relation (i.e., with respect to the data). Recently, a different approach has been introduced, by defining the bilinear term with respect to t...

The importance of multimedia materials in justice is increasing. For example, a security camera recording could provide the evidence needed to clarify a given situation. The problems that arise are linked to the authenticity or intelligibility of the materials. There are situations in which the key material, (for example, a dialogue) is heavily mas...