With the development of intelligent networks such as the Internet of Things, network scales
are becoming increasingly larger, and network environments increasingly complex, which …

We present a Bayesian approach for sparse component analysis (SCA) in the noisy case.
The algorithm is essentially a method for obtaining sufficiently sparse solutions of …

In this paper, we propose a Bayesian pursuit algorithm for sparse representation. It uses
both the simplicity of the pursuit algorithms and optimal Bayesian framework to determine …

This paper addresses the sparse representation (SR) problem within a general Bayesian
framework. We show that the Lagrangian formulation of the standard SR problem, ie, x∗ …

The dimension matching is a tough problem in the vector and matrix computations. In the
traditional mode, there is only one way to calculate the angle between the 1-D plane and the …

The high sampling rate of airborne electromagnetic (AEM) systems can create huge data
volumes, causing major challenges for three-dimensional (3D) electromagnetic modeling …

In this paper, we present a novel approach to voice activity detection (VAD) based on the
sparse representation of an input noisy speech over a learned dictionary. First, we …

Blind identification of the underdetermined mixing matrix is an emerging problem in the area
of sparse component analysis (SCA). Traditionally, the K-hyperLine clustering (K-HLC) …

This paper deals with the design of sensor arrays in the context involving the localization of
a few acoustic sources. Sparse approximation is known to be effective to find the source …

This paper presents the experience at the University of Puerto Rico in Mayaguez with a new
course entitled Technology-Based Entrepreneurship (TBE). This course was developed as …