1 files changed, 42 insertions, 0 deletions
diff --git a/src/modules/audio_processing/aecm/main/matlab/matlab/fallerEstimator.m b/src/modules/audio_processing/aecm/main/matlab/matlab/fallerEstimator.m
new file mode 100644
index 0000000000..d038b519c0
--- /dev/null
+++ b/src/modules/audio_processing/aecm/main/matlab/matlab/fallerEstimator.m
@@ -0,0 +1,42 @@
+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;