Open AccessOptimising compressive sensing matrix using Chicken Swarm Optimisation algorithm
Author(s) -
Aziz Ahmed,
Singh Karan,
Osamy Walid,
Khedr Ahmed M.
Publication year - 2019
Publication title -
iet wireless sensor systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.433
H-Index - 27
ISSN - 2043-6394
DOI - 10.1049/iet-wss.2018.5083
Subject(s) - mutual coherence , compressed sensing , algorithm , matrix (chemical analysis) , coherence (philosophical gambling strategy) , swarm behaviour , computer science , reduction (mathematics) , mathematical optimization , mathematics , materials science , statistics , composite material , geometry
According to compressive sensing (CS) technique, the smaller the mutual coherence between CS matrix and transformer matrix (Φ and Ψ ), the better the performance of CS matrix to reduce the reconstruction error. Generating CS matrix from any distribution may achieve low but not minimum mutual coherence. In this study, using Chicken Swarm Optimisation (CSO), we propose a new efficient CS matrix optimisation algorithm (CSMO‐CSO) to optimise CS matrix by minimising the mutual coherence between Φ and Ψ . The proposed CSMO‐CSO succeeds to minimise the coherence between CS matrix and transformer matrix which improves the CS matrix, and thereby minimise the reconstruction error. The simulation results show that the performance of proposed algorithm exceeds the baseline existing algorithm in terms of mutual coherence reduction and normalised mean square error reduction.