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A novel fast clean algorithm using the gradient descent method
Author(s) -
Choi YoungJae,
Choi InSik
Publication year - 2017
Publication title -
microwave and optical technology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.304
H-Index - 76
eISSN - 1098-2760
pISSN - 0895-2477
DOI - 10.1002/mop.30448
Subject(s) - particle swarm optimization , fast fourier transform , gradient descent , computer science , mathematical optimization , algorithm , descent (aeronautics) , optimization algorithm , engineering , mathematics , artificial intelligence , artificial neural network , aerospace engineering
An evolutionary programming (EP)‐based CLEAN and particle swarm optimization (PSO)‐based CLEAN have better accuracy than the FFT‐based CLEAN. EP‐ and PSO‐based CLEAN have a higher computational burden, because they must solve a three‐dimensional optimization problem using the stochastic search method. To overcome this problem, we employ gradient descent to the CLEAN algorithm. We then compare the performance of the proposed method with that of the PSO‐based CLEAN and the FFT‐based CLEAN. Experimental results show that the proposed algorithm is faster and more accurate than conventional methods. © 2017 Wiley Periodicals, Inc. Microwave Opt Technol Lett 59:1018–1022, 2017