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翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク Auxiliary particle filter ： ウィキペディア英語版 Auxiliary particle filter The auxiliary particle filter is a particle filtering algorithm introduced by Pitt and Shephard in 1999 to improve some deficiencies of the sequential importance resampling (SIR) algorithm when dealing with tailed observation densities. Assume that the filtered posterior is described by the following ''M'' weighted samples: : $$ p(x_t|z_) \approx \sum_^M \omega^_t \delta \left( x_t - x^_t \right). Then, each step in the algorithm consists of first drawing a sample of the particle index $k$ which will be propagated from $t-1$ into the new step $t$. These indexes are auxiliary variables only used as an intermediary step, hence the name of the algorithm. The indexes are drawn according to the likelihood of some reference point $\backslash mu^\_t$ which in some way is related to the transition model $x\_t|x\_$ (for example, the mean, a sample, etc.): : $$ k^ \sim P(i=k|z_t) \propto \omega^_t p( z_t | \mu^_t ) This is repeated for $i=1,2,\backslash dots,M$, and using these indexes we can now draw the conditional samples: : $$ x_t^ \sim p( x | x^). Finally, the weights are updated to account for the mismatch between the likelihood at the actual sample and the predicted point $\backslash mu\_t^\; \backslash propto\; \backslash frac\; .$ ==References== * 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Auxiliary particle filter」の詳細全文を読む スポンサード リンク 翻訳と辞書 : 翻訳のためのインターネットリソース Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.