WienerHammersteinConvolutionOfTwoFiltersParameters

WienerHammersteinConvolutionOfTwoFiltersParameters - 9).

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% part a) in order to obtain a least squares solution obtain the matrix A %clear all N = 300; %# of training data r = 9; A = [-sim_out1(100+r:100+N-1) -sim_out1(100+r-1:100+N-2) -sim_out1(100+r-2:100+N- 3). .. -sim_out1(100+r-3:100+N-4) -sim_out1(100+r-4:100+N-5) -sim_out1(100+r-5:100+N- 6). .. -sim_out1(100+r-6:100+N-7) -sim_out1(100+r-7:100+N-8) -sim_out1(100+r-8:100+N-
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Unformatted text preview: 9). ..-sim_out1(100+r-9:100+N-10) sim_in(100+r+1:100+N) sim_in(100+r:100+N-1) ... sim_in(100+r-1:100+N-2) sim_in(100+r-2:100+N-3) sim_in(100+r-3:100+N-4) ]; b = sim_out1(100+r+1:100+N); prmtrs = A\b % A least squares solution is obtained....
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