A novel fast clean algorithm using the gradient descent method

ABSTRACT 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 sea...

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Bibliographic Details
Published in:Microwave and optical technology letters 2017-05, Vol.59 (5), p.1018-1022
Main Authors: Choi, Young‐Jae, Choi, In‐Sik
Format: Article
Language:English
Subjects:
CLEAN
evolutionary programming
gradient descent
particle swarm optimization
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Summary:ABSTRACT 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
ISSN:0895-2477
1098-2760
DOI:10.1002/mop.30448