Signal Sparse Decomposition Based on Adaptive Chaos Fruit Fly Optimization Algorithm

Sparse decomposition can represent signal with small number of atoms. But, its high computation complexity hinders practical application. Fruit Fly Optimization Algorithm (FOA) improves the efficiency of atoms' searching, but the solution sometimes is not global optimum. In order to solve this problem, Adaptive Chaos Fruit Fly Optimization Algorithm (ACFOA) is presented. In this paper, signal sparse decomposition based on ACFOA is presented. The experiment shows that the reconstructed signal is satisfied, and the computational complexity is reduced greatly