Changed variable name of srcCsd to Svv in obsFiltEst.m

Virtual Sensing/Remote Microphone Technique/MATLAB/Functions/obsFiltEst.m

@@ -28,9 +28,9 @@
 %                          matrix must be NxM, where N is the number of
 %                          virtual microphones and M the number of sources.
 %
-% srcCsd [numeric] (Optional): The source cross spectral density matrix.
-%                              This must be a square (MxM) symmetric matrix
-%                              with the cross power spectral density of the
+% Svv [numeric] (Optional): The source cross spectral density matrix. This
+%                           must be a square (MxM) symmetric matrix with
+%                           the cross power spectral density of the
 %                           sources. [Default: eye(M)]
 % 
 % --------------------------------------------------
@@ -60,7 +60,7 @@
 % Notes
 % 
 % --------------------------------------------------
-function [est, err, errSqr, normErrSqr, See] = obsFiltEst(Pm, O, Pe, srcCsd)
+function [est, err, errSqr, normErrSqr, See] = obsFiltEst(Pm, O, Pe, Svv)
     % ====================================================
     % Check for number of arguments
     % ====================================================
@@ -82,17 +82,17 @@ function [est, err, errSqr, normErrSqr, See] = obsFiltEst(Pm, O, Pe, srcCsd)
         Pe = NaN;
     end
 
-    if nargin > 3 && ~isempty(srcCsd)
-        validateattributes(srcCsd, "numeric", {'2d', 'nonnan', 'finite'}, mfilename, "Source cross spectral density matrix", 3)
+    if nargin > 3 && ~isempty(Svv)
+        validateattributes(Svv, "numeric", {'2d', 'nonnan', 'finite'}, mfilename, "Source cross spectral density matrix", 3)
 
         % Check for correct dimensions
-        if diff(size(srcCsd))
+        if diff(size(Svv))
             error("The source power spectral density matrix must be a square matrix");
-        elseif size(srcCsd, 1) ~= size(Pe, 1)
+        elseif size(Svv, 1) ~= size(Pe, 1)
             error("The number of rows of the source power spectral density matrix must be equal to the number of sources");
         end
     else
-        srcCsd = eye(size(Pe, 2));
+        Svv = eye(size(Pe, 2));
     end
 
 
@@ -110,7 +110,7 @@ function [est, err, errSqr, normErrSqr, See] = obsFiltEst(Pm, O, Pe, srcCsd)
     % Sum of squared estimation errors
     if nargout > 2
         for eIdx = size(Pe, 1):-1:1
-            errSqr(eIdx) = err(eIdx, :) * srcCsd * err(eIdx, :)';
+            errSqr(eIdx) = err(eIdx, :) * Svv * err(eIdx, :)';
         end
 
         errSqr = errSqr.';
@@ -119,7 +119,7 @@ function [est, err, errSqr, normErrSqr, See] = obsFiltEst(Pm, O, Pe, srcCsd)
     % Normalised squared errors
     if nargout > 3
         for eIdx = length(errSqr):-1:1
-            See(eIdx) = Pe(eIdx, :) * srcCsd * Pe(eIdx, :)';
+            See(eIdx) = Pe(eIdx, :) * Svv * Pe(eIdx, :)';
             normErrSqr(eIdx) = errSqr(eIdx)/See(eIdx);
         end