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 …

An algorithm for computing the eigenvalue decomposition of a para-Hermitian polynomial
matrix is described. This amounts to diagonalizing the polynomial matrix by means of a …

This paper proposes a multiresolution form of the singular value decomposition (SVD) and
shows how it may be used for signal analysis and approximation. It is well-known that the …

The problem of paraunitary (PU) filter bank design for subband coding has received
considerable attention in recent years, not least because of the energy preserving property …

Subband decomposition techniques have been extensively used for data coding and
analysis. In most filter banks, the goal is to obtain subsampled signals corresponding to …

Data are said to follow the transform (or analysis) sparsity model if they become sparse
when acted on by a linear operator called a sparsifying transform. Several algorithms have …

An algorithm is presented for computing the singular value decomposition (SVD) of a
polynomial matrix. It takes the form of a sequential best rotation (SBR) algorithm and …

In this paper, a method for approximating a multi-input multi-output (MIMO) transfer function
by a causal finite-impulse response (FIR) paraunitary (PU) system in a weighted least …

The problem of optimizing digital filter banks based on input statistics was perhaps first
addressed nearly four decades ago by Huang and Schultheiss. These authors actually …

This paper proposes a general framework for the optimization of orthonormal filterbanks
(FBs) for given input statistics. This includes as special cases, many previous results on FB …