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LMS

于 2007-09-27 发布文件大小:4KB

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LMS自适应均衡仿真程序,多级抽头,有信噪比条件(LMS adaptive equalizer simulation program, multi-level tap, has SNR)

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LMS算法仿真程序源代码.doc

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LMS_m
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RDPTA
Algorithm Given are P training pairs {X1,d1,X2,d2....Xp,dp}, where Xi is (n*1) di is (n*1) No of Categories=R. i=1,2,...P Yi= Augmented input pattern( obtained by appending 1 to the input vector) i=1,2,…P In the following, k denotes the training step and p denotes the step counter within the training cycle Step 1: c>0 , Emin is chosen, Step 2: Weights are initialized at w at small values, w is (n+1)*1. Counters and error are initialized. k=1,p=1,E=0 Step 3: The training cycle begins here. Input is presented and output computed: Y=Yp, d=dp Oi=f(wtY) for i=1,2,….R Step 4: Weights are updated: wi=wi+1/2c(di-oi)Y for i=1,2,…..R. Step 5: Cycle error is computed: E=1/2(di-oi)2+E for i=1,2,…..R. Step 6: If p<P then p=p+1,k=k+1, and go to Step 3: Otherwise go to Step 7. Step 7: The training cycle is completed. For E=0,terminate the training session. Outputs weights and k. If E>0,then E=0 ,p=1, and enter the new training cycle by going to step 3.

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LMS

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