Year: 2024
Type: article
Abstract: The fixed step size in the sparse adaptive matching pursuit algorithm can result in limited accuracy and overestimation. To address this, this paper proposes a variable-step sparse adaptive matching pursuit algorithm based on the Spearman correlation coefficient. By measuring the Spearman correlation coefficient between the candidate set and the input signal, and introducing an adaptive step size adjustment method based on the parameter values of the correlation coefficient, the performance of the SAMP algorithm is optimized and its adaptability is enhanced. Extensive experiments demonstrate that the proposed method achieves good reconstruction results for one-dimensional sparse signals and two-dimensional images.
Source: Electronics
Authors: Xiaolei Wang, Yingqi Jiang, Guoqiang Ding
Institution: Zhengzhou University of Light Industry
Language: English
Subfield: Computational Mechanics
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,728
OpenAlex ID: W4404498691