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Discrete channel modelling based on genetic algorithm and simulated annealing for training hidden Markov model 下载免费PDF全文
Hidden Markov models (HMMs) have been used to model burst error
sources of wireless channels. This paper proposes a hybrid method of
using genetic algorithm (GA) and simulated annealing (SA) to train
HMM for discrete channel modelling. The proposed method is compared
with pure GA, and experimental results show that the HMMs trained by
the hybrid method can better describe the error sequences due to SA's
ability of facilitating hill-climbing at the later stage of the
search. The burst error statistics of the HMMs trained by the
proposed method and the corresponding error sequences are also
presented to validate the proposed method. 相似文献
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