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[HTML][HTML] Identification of linear and bilinear systems: A unified study
System identification problems are always challenging to address in applications that
involve long impulse responses, especially in the framework of multichannel systems. In this …
involve long impulse responses, especially in the framework of multichannel systems. In this …
Robust widely linear affine projection M-estimate adaptive algorithm: Performance analysis and application
S Lv, H Zhao, W Xu - IEEE Transactions on Signal Processing, 2023 - ieeexplore.ieee.org
The widely-linear affine projection algorithm (WL-APA) based on the orthogonal affine
projection principle and the WL model utilizes the past multiple input signal vectors for …
projection principle and the WL model utilizes the past multiple input signal vectors for …
Identification of room acoustic impulse responses via Kronecker product decompositions
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 …
the framework of many important applications related to the acoustic environment, like echo …
Linear system identification based on a third-order tensor decomposition
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 …
Kronecker product decomposition of the impulse response, together with low-rank …
An improved constrained LMS algorithm for fast adaptive beamforming based on a low rank approximation
S Vadhvana, SK Yadav… - … on Circuits and …, 2022 - ieeexplore.ieee.org
Adaptive beamformers use data from sensor arrays to capture signal from a desired
direction without any distortion, in the presence of interfering signals from other directions in …
direction without any distortion, in the presence of interfering signals from other directions in …
Robust adaptive beamforming based on sparse Bayesian learning and covariance matrix reconstruction
S Ge, C Fan, J Wang, X Huang - IEEE Communications Letters, 2022 - ieeexplore.ieee.org
Sparse Bayesian learning (SBL) exploits sparse information from a Bayesian perspective by
making sparse prior assumptions about the signal. It has good flexibility in modeling sparse …
making sparse prior assumptions about the signal. It has good flexibility in modeling sparse …
Decomposition-based Wiener filter using the Kronecker product and conjugate gradient method
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 …
many applications, like echo cancellation. Recently, the problem has been addressed in the …
Constant-beamwidth kronecker product beamforming with nonuniform planar arrays
In this paper, we address the problem of constant-beamwidth beamforming using
nonuniform planar arrays. We propose two techniques for designing planar beamformers …
nonuniform planar arrays. We propose two techniques for designing planar beamformers …
Robust augmented complex-valued normalized M-estimate subband adaptive filtering algorithm against colored non-circular inputs and impulsive noise
S Lv, H Zhao, W Xu - Journal of the Franklin Institute, 2023 - Elsevier
Recently, the augmented complex-valued normalized subband adaptive filtering (ACNSAF)
algorithm has been proposed to process colored non-circular signals. However, its …
algorithm has been proposed to process colored non-circular signals. However, its …
A high-precision multi-arithmetic neural circuit for the efficient computation of the new filtered-X Kronecker product APL-NLMS algorithm applied to active noise control
In recent years, active noise control (ANC) systems have attracted a lot of attention since
they are considered as potential alternative for solving acoustic noise problems. Until now …
they are considered as potential alternative for solving acoustic noise problems. Until now …