Blind source separation (BSS) is a typical unsupervised learning method that extracts latent
components from their observations. In the meanwhile, convolutive BSS (CBSS) is …

This paper introduces a tensor framework to solve the problem of nonunitary joint block
diagonalization (JBD) of a set of real or complex valued matrices. We show that JBD can be …

Convolutive blind source separation (CBSS) is one of the main branches in the field of
intelligent signal processing. Inspired by the thought of sliding discrete Fourier transform …

This article addresses the problem of the non-unitary joint block diagonalization of a given
set of complex matrices. Two new algorithms are provided: the first is based on a classical …

This paper addresses robust adaptive beamforming for passive sonar in uncertain, shallow-
water environments. Conventional beamforming is still common in passive sonar because …

We consider the problem of non-orthogonal joint diagonalization of a set of complex
matrices. This appears in many signal processing problems and is instrumental in source …

Approximate joint block diagonalization (AJBD) of a set of matrices has applications in blind
source separation, eg, when the signal mixtures contain mutually independent subspaces of …

This paper takes a close look at the block Toeplitz structure and block-inner diagonal
structure of auto correlation matrices of source signals in convolutive blind source …

Tensor diagonalization means transforming a given tensor to an exactly or nearly diagonal
form through multiplying the tensor by non-orthogonal invertible matrices along selected …

In this paper, we consider the problem of non-orthogonal joint diagonalization of a set of
hermitian matrices. This appears in many blind signal processing problems as source …