期刊
JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
卷 91, 期 12, 页码 2345-2360出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/00949655.2021.1894563
关键词
Blind deconvolution; Monte Carlo sequential importance sampling; redrawing; rejection control; resampling
资金
- National Natural Science Foundation of China [71671183, 71874184, 11201478, 11471030]
- Chinese Universities Scientific Fund [2016LX002]
This paper introduces a new sequential importance sampling algorithm named RR-RC-SIS, which shows advantages in sampling computation speed and maintaining sample diversity. Numerical simulation on blind deconvolution problem in digital communications demonstrates the practical value of the algorithm.
Monte Carlo computation has been widely applied in the field of dynamic systems. This paper focuses on the general framework in the implementation of sequential importance sampling by combining redrawing, resampling and rejection control simultaneously. The proposed algorithm is named as Redrawing Resampling Rejection Controlled Sequential Importance Sampling (RR-RC-SIS). It can reduce sampling computation and meanwhile maintain the diversity of random samples. Theoretical basis is given to prove that RR-RC-SIS has advantages in comparison with Rejection Controlled Sequential Importance Sampling. It also has practical value as illustrated in numerical simulation on blind deconvolution problem in digital communications.
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