首页> 外文期刊>Journal of statistical computation and simulation >Redrawing-resampling rejection controlled sequential importance sampling
【24h】

Redrawing-resampling rejection controlled sequential importance sampling

机译:重绘重新采样抑制控制顺序重要性采样

获取原文
获取原文并翻译 | 示例
           

摘要

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.
机译:Monte Carlo Comparation已广泛应用于动态系统领域。 本文侧重于通过同时结合重绘,重采样和拒绝控制来实现顺序重要性采样的一般框架。 所提出的算法被命名为重定相制重新采样抑制控制顺序重点采样(RR-RC-SIS)。 它可以减少采样计算,同时维持随机样本的多样性。 理论基础是证明RR-RC-SIS与拒绝控制连续的重视采样相比具有优势。 它还具有实用的价值,如数字通信中的盲解卷积问题的数值模拟中所示。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号