MATLAB: Differential evalution code Error using * Inner matrix dimensions must agree.

deerror

Error in @(x)sum((minus((x(1)),V)*sin(2.*pi.*x(2).*t+x(3)).^2))/n Error in noise_de (line 56) pop(i).Cost=CostFunction(pop(i).Position);
  1. clear all; close all; clc
  3. fs=200; %sampling freq.
  4. dt =1/fs;
  5. n=fs/3 %number of samples/cycle
  6. m=3 %no. of cycles
  7. fi=50;
  8. t = dt*(0:400); %data window
  10. ww=wgn(201,1,-40);
  11. size(transpose(ww))
  12. t =dt*(0:200);
  13. y=sin(2*pi*fi*t + 0.3);
  14. for j=0:200/(n*m)
  15. t =dt*(j*m*n:(j+1)*m*n);
  16. x=sin(2*pi*fi*t + 0.3)+transpose(wgn(1+n*m,1,-40));
  17. V=x
  19. tmax=0.01;
  20. lastreported=0;
  21. %% Problem Definition
  22. t_est=[];
  23. f_est=[];
  24. dt=1/fs;
  25. i_max=tmax*fs
  26. for ii=0:i_max
  27. if(ii/i_max*100-lastreported>=1)
  28. lastreported=ii/i_max*100;
  29. fprintf('%5.2f%%\n',lastreported);
  30. end
  31. t=(ii:ii+n-1)*dt;
  33. CostFunction=@(x) sum((minus((x(1)),V)*sin(2*pi.*x(2).*t+x(3)).^2))/n; % Cost Function
  34. nVar=3; % Number of Decision Variables
  35. VarSize=[1 nVar]; % Decision Variables Matrix Size
  36. VarMin=[0,48,0]; % Lower Bound of Decision Variables
  37. VarMax=[1000,52,2*pi]; % Upper Bound of Decision Variables
  39. %% DE Parameters
  41. MaxIt=200; % Maximum Number of Iterations
  42. nPop=50; % Population Size
  43. beta=0.5; % Scaling Factor
  44. pCR=0.2; % Crossover Probability
  45. minCost=1e-10;
  46. %% Initialization
  48. empty_individual.Position=[];
  49. empty_individual.Cost=[];
  51. BestSol.Cost=inf;
  52. pop=repmat(empty_individual,nPop,1);
  54. for i=1:nPop
  55. pop(i).Position=unifrnd(VarMin,VarMax,VarSize);
  56. pop(i).Cost=CostFunction(pop(i).Position);
  57. if pop(i).Cost<BestSol.Cost
  58. BestSol=pop(i);
  59. end
  60. end
  61. BestCost=zeros(MaxIt,1);
  63. %% DE Main Loop
  65. for it=1:MaxIt
  66. for i=1:nPop
  67. x=pop(i).Position;
  68. A=randperm(nPop);
  69. A(A==i)=[];
  70. a=A(1);
  71. b=A(2);
  72. c=A(3);
  73. % Mutation
  74. %beta=unifrnd(beta_min,beta_max);
  75. y=pop(a).Position+beta.*(pop(b).Position-pop(c).Position);
  76. y = max(y, VarMin);
  77. y = min(y, VarMax);
  78. % Crossover
  79. z=zeros(size(x));
  80. j0=randi([1 numel(x)]);
  81. for j=1:numel(x)
  82. if j==j0 || rand<=pCR
  83. z(j)=y(j);
  84. else
  85. z(j)=x(j);
  86. end
  87. end
  88. NewSol.Position=z;
  89. NewSol.Cost=CostFunction(NewSol.Position);
  91. if NewSol.Cost<pop(i).Cost
  92. pop(i)=NewSol;
  93. if pop(i).Cost<BestSol.Cost
  94. BestSol=pop(i);
  95. end
  96. end
  98. end
  100. % Update Best Cost
  101. BestCost(it)=BestSol.Cost;
  102. % Show Iteration Information
  103. %disp(['Iteration ' num2str(it) ': Best Cost = ' num2str(BestCost(it))]);
  104. if(minCost>BestSol.Cost)
  105. break;
  106. ErrorTarget=0.00000001;
  107. EvalMax=10000*n;
  108. end
  110. end
  111. %% Show Results
  112. % disp(['Iteration ' num2str(ii) ': Best Cost = ' num2str(BestSol.Position(2))]);
  113. t_est=[t_est;(ii)*dt];
  114. f_est=[f_est;BestSol.Position(2)];
  115. if(minCost>BestSol.Cost)
  116. %break;
  117. ErrorTarget=0.00000001;
  118. EvalMax=10000*n;
  119. end
  120. end
  121. end
  122. t_est
  123. f_est
  124. plot (t_est,f_est,'red')
  126. hold on
  128. xlabel('time')
  129. ylabel('frequency')
  130. title('DE white noise ')
  131. c=vpa(rms(fi(t_est)-f_est))
  132. plot (t_est,fi*ones(size(t_est)))
  133. hold off

Best Answer

@(x)sum((minus((x(1)),V).*sin(2.*pi.*x(2).*t+x(3)).^2))/n
%                       ^
%                       |
%                       ------- Elementwise multiplication
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