annotate toolboxes/FullBNT-1.0.7/Kalman/learn_AR_diagonal.m @ 0:cc4b1211e677
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646 (e263d8a21543) added further path and more save "camirversion.m"
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Daniel Wolff |
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Fri, 19 Aug 2016 13:07:06 +0200 |
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1 function [coef, C] = learn_AR_diagonal(y, k)
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2 % Find the ML parameters for a collection of independent scalar AR processes.
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3
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4 % sep_coef(1,1,t,i) is the coefficient to apply to compopnent i of the state vector t steps ago
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5 % eg. consider two components L and R and let A = coef(:,:,1,:), B = coef(:,:,2,:)
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6 % L3 (AL 0 BL 0) (L2) (CL 0 0 0)
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7 % R3 = (0 AR 0 BR) (R2) (0 CR 0 0)
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8 % L2 (1 0 0 0 ) (L1) + (0 0 0 0)
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9 % R2 (0 1 0 0 ) (R1) (0 0 0 0)
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10
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11 ss = size(y, 1);
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12 sep_coef = zeros(1,1,k,ss);
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13 for i=1:ss
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14 [sep_coef(:,:,:,i), sep_cov(i)] = learn_AR(k, y(i,:));
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15 end
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16 C = diag(sep_cov);
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17 for t=1:k
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18 x = sep_coef(1,1,t,:);
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19 coef(:,:,t) = diag(x(:));
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20 end
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