基于Matlab实现PSO和DWT信号去噪仿真（源码+数据）.rar

function position = PSO(signal, z, popsize, iterations, printflag) %% Function to calculate the position required for maximum SNR %% if printflag == 1 fprintf('--- Setting up PSO parameters ---\n'); end nVar=2; % Number of Decision Variables0 VarSize=[1 nVar]; % Size of Decision Variables Matrix Var1Min=1; % Lower Bound of Variables Var1Max= fix(log2(length(signal))); % Upper Bound of Variables %Var1Max=5; Var2Min=-(max(z)*2); Var2Max=-Var2Min; %PSO Params MaxIt=iterations; % Iterations nPop=popsize; % (Swarm Size) w=1; % Inertia Weight wdamp=0.99; % Inertia Weight Damping Ratio c1=1.1; % Learning Coefficient c2=1.6; % Learning Coefficient Vel1Max=0.1*(Var1Max-Var1Min); Vel1Min=-Vel1Max; Vel2Max=0.1*(Var2Max-Var2Min); Vel2Min=-Vel2Max; empty_particle.Position=[]; empty_particle.Cost=[]; empty_particle.Velocity=[]; empty_particle.Best.Position=[]; empty_particle.Best.Cost=[]; particle=repmat(empty_particle,nPop,1); GlobalBest.Cost=-inf; if printflag == 1 fprintf('--- Setting initial parameters ---\n'); end for i=1:nPop particle(i).Position=unifrnd([Var1Min, Var2Min],[Var1Max, Var2Max]); particle(i).Position(1)=ceil(particle(i).Position(1)); particle(i).Velocity=zeros(VarSize); particle(i).Cost=CostFunction(signal,z,particle(i).Position); particle(i).Best.Position=particle(i).Position; particle(i).Best.Cost=particle(i).Cost; if particle(i).Best.Cost>GlobalBest.Cost GlobalBest=particle(i).Best; end if printflag == 1 fprintf('--- Completed setting up particle %d ---\n',i); end end BestCost=zeros(MaxIt,1); if printflag == 1 fprintf('--- Starting PSO ---\n'); end for it=1:MaxIt for i=1:nPop particle(i).Velocity = w*particle(i).Velocity ... +c1*rand(VarSize).*(particle(i).Best.Position-particle(i).Position) ... +c2*rand(VarSize).*(GlobalBest.Position-particle(i).Position); particle(i).Velocity(1) = max(particle(i).Velocity(1),Vel1Min); particle(i).Velocity(1) = min(particle(i).Velocity(1),Vel1Max); particle(i).Velocity(2) = max(particle(i).Velocity(2),Vel2Min); particle(i).Velocity(2) = min(particle(i).Velocity(2),Vel2Max); particle(i).Position = particle(i).Position + particle(i).Velocity; if particle(i).Position(1)<Var1Min || particle(i).Position(1)>Var1Max particle(i).Velocity(1) = -particle(i).Velocity(1); end if particle(i).Position(2)<Var2Min || particle(i).Position(2)>Var2Max particle(i).Velocity(2) = -particle(i).Velocity(2); end particle(i).Position(1) = ceil(particle(i).Position(1)); particle(i).Position(1) = max(particle(i).Position(1),Var1Min); particle(i).Position(1) = min(particle(i).Position(1),Var1Max); particle(i).Position(2) = max(particle(i).Position(2),Var2Min); particle(i).Position(2) = min(particle(i).Position(2),Var2Max); particle(i).Cost = CostFunction(signal,z,particle(i).Position); if particle(i).Cost>particle(i).Best.Cost particle(i).Best.Position=particle(i).Position; particle(i).Best.Cost=particle(i).Cost; if particle(i).Best.Cost>GlobalBest.Cost GlobalBest=particle(i).Best; end end if printflag == 1 fprintf('--- Iteration %d Particle %d Position %d %d Velocity %d %d Cost %d ---\n',it,i,particle(i).Position(1),particle(i).Position(2),particle(i).Velocity(1), particle(i).Velocity(2),particle(i).Cost); end end BestCost(it)=GlobalBest.Cost; if printflag == 1 fprintf('Iteration %d Best Cost %d ---\n',it,BestCost(it)); end w=w*wdamp; end position = GlobalBest; end