- refactored

common/statistic/hmm_eval.m

@@ -0,0 +1,53 @@
+## Copyright (C) 2017 Jens Ahrensfeld
+## 
+## This program is free software; you can redistribute it and/or modify it
+## under the terms of the GNU General Public License as published by
+## the Free Software Foundation; either version 3 of the License, or
+## (at your option) any later version.
+## 
+## This program is distributed in the hope that it will be useful,
+## but WITHOUT ANY WARRANTY; without even the implied warranty of
+## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+## GNU General Public License for more details.
+## 
+## You should have received a copy of the GNU General Public License
+## along with this program.  If not, see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*- 
+## @deftypefn {Function File} {@var{retval} =} hmm_eval (@var{input1}, @var{input2})
+##
+## @seealso{}
+## @end deftypefn
+
+## Author: Jens Ahrensfeld <ahrensfeld@w2ess001vm>
+## Created: 2017-06-14
+
+function sv = hmm_eval (A, numIter)
+
+numStates = length(A)
+C = zeros(1,numStates);
+
+#A = rand(numStates, numStates)
+
+for s=1:numStates,
+	A(s,:) = A(s,:) ./ sum(A(s,:));
+	[AS(s,:), Ai(s,:)] = sort(A(s,:));
+	AC(s,:) = cumsum(AS(s,:));
+end
+
+A
+AC
+s=1;
+for n=1:numIter,
+	sv(n) = s;
+	stateProbs = AC(s,:);
+	z = rand();
+	c = find (z <= stateProbs);
+	s = Ai(s, c(1));
+	C(s) = C(s) + 1;
+end
+
+plot(1:numIter, sv, 'ro-'); grid;
+C=C/numIter
+
+endfunction

common/statistic/movingavg.m

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+function [y, zf] = movingavg(x, zi)
+	if ~isstruct(zi)
+		N = zi;
+		zf = struct('N', N, 's', zeros(N+1, 1), 'ri', 2, 'wi', 1, 'y', 0);
+	else
+		zf = zi;
+	end
+	
+	xn = x/zf.N;
+	zf.y = zf.y + xn - zf.s(zf.ri);
+	y = zf.y;
+	
+	zf.ri = zf.ri + 1;
+	if zf.ri > length(zf.s)
+		zf.ri = 1;
+	end
+	
+	zf.s(zf.wi) = xn;
+	zf.wi = zf.wi + 1;
+	if zf.wi > length(zf.s)
+		zf.wi = 1;
+	end
+

common/statistic/rms.m

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+% Power estimation on discrete signals
+function y = rms(x,Nw)
+
+N = length(x);
+y = zeros(1,N);
+
+y(1) = x(1)^2;
+
+for k = 2:N-Nw,
+  for n = k:Nw+k,
+    y(n) = y(n-1)*(1-1/Nw) + 1/Nw*x(n)^2;
+  end;
+end;

common/statistic/sm.m

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+% Power estimation on discrete signals
+function [y,yf] = rms(x,Nw,yi)
+
+N = length(x);
+y = zeros(1,N);
+
+
+Nb = ceil(N/Nw);
+xp = zeros(1,Nb*Nw);
+yp = zeros(1,Nb*Nw);
+
+xp(1:N) = x(1:N);
+yp(1) = abs(x(1));
+
+for k = 1:Nb-1,
+  for n = (k-1)*Nw+2:k*Nw+2,
+    yp(n) = yp(n-1)*(1-1/Nw) + 1/Nw*abs(x(n));
+  end;
+end;
+
+y = yp(1:N);

common/statistic/sm2.m

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+% Power estimation on discrete signals
+function [y,yf] = sm2(x,yi,arf)
+
+N = length(x);
+x(1) = x(1) + yi*(1/arf-1);
+x = abs(x);
+a = [1,-(1-arf)];
+y = filter(arf,a,x);
+yf = y(N);

common/statistic/smhs.m

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+% Power estimation on discrete signals
+function [y,yf] = smhs(x,Nw1,Nw2,yi)
+
+N = length(x);
+y = zeros(1,N);
+x = abs(x);
+
+if (x(1) > yi) 
+  y(1) = (1-1/Nw1)*yi + (1/Nw1)*x(1);
+else
+  y(1) = (1-1/Nw2)*yi + (1/Nw2)*x(1);
+end;
+
+for n = 2:N,
+    if (x(n) > y(n-1)) 
+      y(n) = (1-1/Nw1)*y(n-1) + (1/Nw1)*x(n);
+    else
+      y(n) = (1-1/Nw2)*y(n-1) + (1/Nw2)*x(n);
+    end;
+end;
+yf = y(N);