Eigenvalue decomposition of a parahermitian matrix: Extraction of analytic eigenvectors
An analytic parahermitian matrix admits in almost all cases an eigenvalue decomposition
(EVD) with analytic eigenvalues and eigenvectors. We have previously defined a discrete …
(EVD) with analytic eigenvalues and eigenvectors. We have previously defined a discrete …
Polynomial eigenvalue decomposition for multichannel broadband signal processing: A mathematical technique offering new insights and solutions
This article is devoted to the polynomial eigenvalue decomposition (PEVD) and its
applications in broadband multichannel signal processing, motivated by the optimum …
applications in broadband multichannel signal processing, motivated by the optimum …
Signal compaction using polynomial EVD for spherical array processing with applications
Multi-channel signals captured by spatially separated sensors often contain a high level of
data redundancy. A compact signal representation enables more efficient storage and …
data redundancy. A compact signal representation enables more efficient storage and …
Polynomial eigenvalue decomposition-based target speaker voice activity detection in the presence of competing talkers
Voice activity detection (VAD) algorithms are essential for many speech processing
applications, such as speaker diarization, automatic speech recognition, speech …
applications, such as speaker diarization, automatic speech recognition, speech …
A polynomial subspace projection approach for the detection of weak voice activity
A voice activity detection (VAD) algorithm identifies whether or not time frames contain
speech. It is essential for many military and commercial speech processing applications …
speech. It is essential for many military and commercial speech processing applications …
Postfilter for Dual Channel Speech Enhancement Using Coherence and Statistical Model-Based Noise Estimation
A multichannel speech enhancement system usually consists of spatial filters such as
adaptive beamformers followed by postfilters, which suppress remaining noise. Accurate …
adaptive beamformers followed by postfilters, which suppress remaining noise. Accurate …
Kronecker-product beamforming with sparse concentric circular arrays
This article presents a Kronecker-product (KP) beamforming approach incorporating sparse
concentric circular arrays (SCCAs). The locations of the microphones on the SCCA are …
concentric circular arrays (SCCAs). The locations of the microphones on the SCCA are …
On intrusive speech quality measures and a global SNR based metric
Measuring the quality of noisy speech signals has been an increasingly important problem
in the field of speech processing as more and more speech-communication and human …
in the field of speech processing as more and more speech-communication and human …
Speech enhancement in distributed microphone arrays using polynomial eigenvalue decomposition
As the number of connected devices equipped with multiple microphones increases,
scientific interest in distributed microphone array processing grows. Current beamforming …
scientific interest in distributed microphone array processing grows. Current beamforming …
Low-rank para-hermitian matrix EVD via polynomial power method with deflation
The power method in conjunction with deflation provides an economical approach to
compute an eigenvalue decomposition (EVD) of a low-rank Hermitian matrix, which typically …
compute an eigenvalue decomposition (EVD) of a low-rank Hermitian matrix, which typically …