Abstract
The main problem of time-frequency atom decomposition (TFAD) lies in an extremely high computational load. This paper presents a fast implementation method based on quantum-inspired genetic algorithm (QGA). Instead of finding the optimal atom in greedy implementation algorithm, this method is to search a satisfactory atom in every iteration of TFAD. Making full use of QGA's advantages such as good global search capability, rapid convergence and short computing time, the method reduces greatly the computational load of TFAD. Experiments conducted on radar emitter signals verify the effectiveness and practicality of the introduced method. © Springer-Verlag Berlin Heidelberg 2007.
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CITATION STYLE
Zhang, G., & Rong, H. (2007). Quantum-inspired genetic algorithm based time-frequency atom decomposition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4490 LNCS, pp. 243–250). Springer Verlag. https://doi.org/10.1007/978-3-540-72590-9_35
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