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function [U, Hnew] = fallerEstimator(Y, X, H, mu)
% Near end signal is stacked frame by frame columnwise in matrix Y and far end in X
%
% Possible estimation procedures are
% 1) LSE
% 2) NLMS
% 3) Separated numerator and denomerator filters
regParam = 1;
[numFreqs, numFrames] = size(Y);
[numFreqs, Q] = size(X);
U = zeros(numFreqs, 1);
if ((nargin == 3) | (nargin == 5))
dtd = 0;
end
if (nargin == 4)
dtd = H;
end
Emax = 7;
dEH = Emax-sum(sum(H));
nu = 2*mu;
% if (nargin < 5)
% H = zeros(numFreqs, Q);
% for kk = 1:numFreqs
% Xmatrix = hankel(X(kk,1:Q),X(kk,Q:end));
% y = Y(kk,1:end-Q+1)';
% H(kk,:) = (y'*Xmatrix')*inv(Xmatrix*Xmatrix'+regParam);
% U(kk,1) = H(kk,:)*Xmatrix(:,1);
% end
% else
for kk = 1:numFreqs
x = X(kk,1:Q)';
y = Y(kk,1);
Htmp = mu*(y-H(kk,:)*x)/(x'*x+regParam)*x;
%Htmp = (mu*(y-H(kk,:)*x)/(x'*x+regParam) - nu/dEH)*x;
H(kk,:) = H(kk,:) + Htmp';
U(kk,1) = H(kk,:)*x;
end
% end
Hnew = H;
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