A millimeter wave (mm-wave) communication system provides multi-Gb/s data rates in short-
distance transmission. Because millimeter waves have short wavelength, transceivers can …

ABSTRACT Niklaus Emil Wirth introduced the innovative concept of Programming=
Algorithm+ Data Structure [109]. Inspired by this, we advance the concept to the next level by …

Orthogonal Matching Pursuit (OMP) is an important compressive sensing (CS) recovery and
sparsity inducing algorithm, which has potential in various emerging applications ranging …

Based on the efficient inverse Cholesky factorization, we propose an implementation of OMP
(called as version 0, ie, v0) and its four memory-saving versions (ie, the proposed v1, v2, v3 …

Low-complexity compressed sensing (CS) techniques for monitoring electrocardiogram
(ECG) signals in wireless body sensor network (WBSN) are presented. The prior probability …

To solve the disturbed time-varying inversion problem, an exponential-type anti-noise
varying-gain network (EAVGN) is proposed and analyzed. To do so, a vector-based error …

Compressive sensing (CS) has recently become a critical technique to reduce the high
computational cost of signal processing systems. One of the main signal processing …

This study aims to develop an accurate framework for respiratory rate (RR) monitoring from
the photoplethysmogram (PPG). Sparse signal reconstruction (SSR) is used to obtain a …

Reconstruction algorithms of compressively sampled data include solving a sparse
approximation problem. This problem requires iterative search or optimization techniques …

Compressive Sensing (CS) is a novel scheme, in which a signal that is sparse in a known
transform domain can be reconstructed using fewer samples. However, the signal …