Update obsFilt.m to accept matrix SNR values and change input check for...

Update obsFilt.m to accept matrix SNR values and change input check for regularisation factors to check for real values

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

@@ -3,7 +3,7 @@
 % Author: Achilles Kappis
 % e-mail: axilleaz@protonmail.com
 %
-% Date: 14/02/2025 (DD/MM/YYYY)
+% Date: 05/03/2025 (DD/MM/YYYY)
 %
 % Copyright: MIT
 % --------------------------------------------------
@@ -41,12 +41,13 @@
 %                              Signal-to-Noise Ratio (SNR) in the
 %                              monitoring microphone signals. This must
 %                              be either a scalar indicating the common
-%                              SNR value of the microphone signals, or a
+%                              SNR value of the microphone signals, a
 %                              vector of dimensions Kx1, containing the SNR
-%                              values of each microphone. The values must
-%                              be real or Inf for the noiseless case. See
-%                              the Notes below for references on how this
-%                              value is calculated. [Default: Inf].
+%                              values of each microphone or a square matrix
+%                              with dimensions KxK. The values must be real
+%                              or Inf for the noiseless case. See the Notes
+%                              below for references on how this value is
+%                              calculated. [Default: Inf].
 % 
 % --------------------------------------------------
 % Output
@@ -106,7 +107,7 @@ function [oOpt, Sme, Smm, condNum] = obsFilt(Pe, Pm, Svv, regFacs, snrVal)
     end
 
     if nargin > 3 && ~isempty(regFacs)
-        validateattributes(regFacs, "numeric", {'2d', 'nonnan', 'nonempty', 'finite'}, mfilename, "Regularisation factors", 4);
+        validateattributes(regFacs, "numeric", {'2d', 'real', 'nonnan', 'nonempty', 'finite'}, mfilename, "Regularisation factors", 4);
 
         % Make sure regFacs has correct dimensions
         if ~isscalar(regFacs)
@@ -121,15 +122,23 @@ function [oOpt, Sme, Smm, condNum] = obsFilt(Pe, Pm, Svv, regFacs, snrVal)
     end
 
     if nargin > 4 && ~isempty(snrVal)
-        validateattributes(snrVal, "numeric", {'vector', 'real', 'nonnan', 'nonempty'}, mfilename, "Normalised Root-Mean-Square Singal-to-Noise Ratio of the monitoring microphones", 5);
-
-        % Make sure snrVal has correct dimensions
+        validateattributes(snrVal, "numeric", {'2d', 'real', 'nonnan', 'nonempty'}, mfilename, "Normalised Root-Mean-Square Singal-to-Noise Ratio of the monitoring microphones", 5);
+        
         if ~isscalar(snrVal) && numel(snrVal) ~= size(Pm, 1)
             error("SNR must be either a scalar or its length must match the number of monitoring microphones.");
         end
 
-        if sum(snrVal == -Inf) > 0
-            error("SNR value cannot be equal to -Inf");
+        % Make sure snrVal has correct dimensions
+        if ~isscalar(snrVal)
+            if isvector(snrVal) && numel(snrVal) ~= size(Pm, 1)
+                error("If the SNR values are given as a vector the number of elements must match the number of monitoring microphones.");
+            elseif ismatrix(snrVal) && ~isequal(size(snrVal), ones(1, 2) .* size(Pm, 1))
+                error("If the SNR values are given as a matrix, it must be a square matrix with each dimension equal to the number of monitoring microphones.");
+            end
+        end
+
+        if nnz(snrVal == -Inf)
+            error("SNR value cannot be equal -Inf");
         end
     else
         snrVal = Inf;
@@ -156,12 +165,18 @@ function [oOpt, Sme, Smm, condNum] = obsFilt(Pe, Pm, Svv, regFacs, snrVal)
 
     % Signal-to-Noise Ratio at the monitoring microphones
     if ~isinf(snrVal)
-        snrVal = 10^(-snrVal/10); % Convert deciBel to linear
+        snrVal = 10.^(-snrVal/10); % Convert deciBel to linear
         snrMtx = (snrVal.^2) .* norm(Smm, 'fro')/(size(Pm, 1)^2); % Calculate the appropriate SNR amplitude values
     else
         snrMtx = 0;
     end
-    snrMtx = snrMtx .* eye(size(Pm, 1));
+
+    if isscalar(snrMtx)
+        snrMtx = snrMtx .* eye(size(Pm, 1));
+    elseif isvector(snrMtx)
+        snrMtx = diag(snrMtx);
+    end
+
     Smm = Smm + snrMtx + regMat;
     oOpt = Sme/Smm;