Nowadays, a large amount of information has to be transmitted or processed. This implies
high-power processing, large memory density, and increased energy consumption. In …

This article proposes an improved orthogonal matching pursuit (OMP) algorithm and its
implementation with Xilinx Vivado high-level synthesis (HLS). We use the Gram-Schmidt …

Machine learning techniques have advanced rapidly, leading to better prediction accuracy
within a short computational time. Such advancement encourages various novel …

In this paper, two neurodynamic algorithms and the corresponding Field-Programmable-
Gate-Array (FPGA) implementation scheme are presented, respectively. Firstly, based on …

Sparse recovery algorithms are integral to compressed sensing (CS) as they facilitate the
reconstruction of higher dimensional signals from sub-Nyquist measurements. Although …

The long-term operating structural health monitoring (SHM) system generates massive
monitoring data, whose transmission and storage are challenging tasks. To address this …

The increased use of multimedia applications to share digital images has raised concerns
about their security during transmission and storage as well. Thus, the need for integrating …

Aiming at the problems of low signal precision and uncertain sparsity in traditional structural
damage identification methods, a structural damage identification method based on an …

This paper introduces an innovative image compression and encryption algorithm that
leverages the genetic algorithm (GA), compressive sensing (CS), and a newly developed …

In this paper, the Floating-Point Core Architecture based QR decomposition is proposed for
solving least square problems in the Orthogonal Matching Pursuit algorithm (OMP-FPCA …