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hybridSIREKF

于 2007-09-30 发布 文件大小:40KB
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代码说明:

   To estimate the input-output mapping with inputs x % and outputs y generated by the following nonlinear, % nonstationary state space model: % x(t+1) = 0.5x(t) + [25x(t)]/[(1+x(t))^(2)] % + 8cos(1.2t) + process noise % y(t) = x(t)^(2) / 20 + 6 squareWave(0.05(t-1)) + 3 % + time varying measurement noise % using a multi-layer perceptron (MLP) and both the EKF and % the hybrid importance-samping resampling (SIR) algorithm. (To estimate the input-output mapping with inputs x and outputs y generated by the following nonlinear, nonstationary state space model: x (t+ 1) = 0.5x (t)+ [25x (t )]/[( 1+ x (t)) ^ (2)]+ 8cos (1.2t)+ process noise y (t) = x (t) ^ (2)/20+ 6 squareWave (0.05 (t-1 ))+ 3+ time varying measurement noise using a multi-layer perceptron (MLP) and both the EKF and the hybrid importance-samping resampling (SIR) algorithm.)

文件列表:

demo2
.....\#sirdemo2.m#
.....\gradupdate.m
.....\hybridsir.m
.....\mlp.m
.....\mlpekf.m
.....\mlph.m
.....\mlpratios.m
.....\predictmlp.m
.....\resamplemlp.m
.....\sirdemo2.m

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