From 029a30426b2f6497c8237e7d49b10f79f9e5bee5 Mon Sep 17 00:00:00 2001
From: ZaellixA <axilleaz@protonmail.com>
Date: Wed, 5 Mar 2025 00:36:41 +0000
Subject: [PATCH] Update obsFilt.m to accept matrix SNR values and change input
check for regularisation factors to check for real values
---
.../MATLAB/Functions/obsFilt.m | 43 +++++++++++++------
1 file changed, 29 insertions(+), 14 deletions(-)
diff --git a/Virtual Sensing/Remote Microphone Technique/MATLAB/Functions/obsFilt.m b/Virtual Sensing/Remote Microphone Technique/MATLAB/Functions/obsFilt.m
index f2ef019..b71fcce 100644
--- a/Virtual Sensing/Remote Microphone Technique/MATLAB/Functions/obsFilt.m
+++ b/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;
--
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