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Hardware accelerators for real-time face recognition: A survey
Real-time face recognition has been of great interest in the last decade due to its wide and
varied critical applications which include biometrics, security in public places, and …
varied critical applications which include biometrics, security in public places, and …
[HTML][HTML] Relevance of polynomial matrix decompositions to broadband blind signal separation
The polynomial matrix EVD (PEVD) is an extension of the conventional eigenvalue
decomposition (EVD) to polynomial matrices. The purpose of this article is to provide a …
decomposition (EVD) to polynomial matrices. The purpose of this article is to provide a …
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 …
A comparative study on CORDIC algorithms and applications
Jack Edward Volder had introduced the CORDIC (COordinate Rotation DIgital Computer) in
1959. This year, critical development and advancement of the CORDIC algorithm have …
1959. This year, critical development and advancement of the CORDIC algorithm have …
Radix-4 CORDIC algorithm based low-latency and hardware efficient VLSI architecture for Nth root and Nth power computations
In this article, a low-complexity VLSI architecture based on a radix-4 hyperbolic COordinate
Rotion DIgital Computer (CORDIC) is proposed to compute the N th root and N th power of a …
Rotion DIgital Computer (CORDIC) is proposed to compute the N th root and N th power of a …
Efficient implementation of iterative polynomial matrix evd algorithms exploiting structural redundancy and parallelisation
A number of algorithms are capable of iteratively calculating a polynomial matrix eigenvalue
decomposition (PEVD), which is a generalisation of the EVD and will diagonalise a …
decomposition (PEVD), which is a generalisation of the EVD and will diagonalise a …
Support estimation of analytic eigenvectors of parahermitian matrices
Extracting analytic eigenvectors from parahermitian matrices relies on phase smoothing in
the discrete Fourier transform (DFT) domain as its most expensive algorithmic component …
the discrete Fourier transform (DFT) domain as its most expensive algorithmic component …
Fast givens rotation approach to second order sequential best rotation algorithms
The second order sequential best rotation (SBR2) algorithm is a popular algorithm to
decompose a parahermitian matrix into approximate polynomial eigenvalues and …
decompose a parahermitian matrix into approximate polynomial eigenvalues and …
Neural Networks for Computing Eigenvalues of Parahermitian Matrices
Calculating the eigenvalues and eigenvectors of a polynomial matrix has proved to be an
important problem in signal processing, in recent years. There exists various iterative …
important problem in signal processing, in recent years. There exists various iterative …
High-performance matrix eigenvalue decomposition using the parallel jacobi algorithm on fpga
D Yan, WX Wang, XW Zhang - Circuits, Systems, and Signal Processing, 2023 - Springer
Field-programmable gate arrays (FPGAs) are one attractive hardware platform for computing
the eigenvalue decomposition of low-dimensional symmetric matrices. For this, one popular …
the eigenvalue decomposition of low-dimensional symmetric matrices. For this, one popular …