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Signal Detection Performance and Monte-Carlo Simulation

Explore detection performance metrics using Monte-Carlo simulation. Calculate probabilities of detection for various signal-to-noise ratios. Plot performance curves and analyze relative errors.

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Signal Detection Performance and Monte-Carlo Simulation

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  1. 8.3 detection performance and monte-carlo simulation In example 8.2:

  2. N=8; pf=0:0.01:1; d=0; pd1=Q(Qinv(pf)-sqrt(N).*d); % function y=Qinv(x) % y=sqrt(2).*erfinv(1-2.*x); d=0.2; pd2=Q(Qinv(pf)-sqrt(N).*d); d=0.5; pd3=Q(Qinv(pf)-sqrt(N).*d); d=1; pd4=Q(Qinv(pf)-sqrt(N).*d); plot(pf,pd1,'k',pf,pd2,'k',pf,pd3,'k',pf,pd4,'k','linewidth',1) grid xlabel('P_F') ylabel('P_D')

  3. 信噪比d 检测性能曲线

  4. Define relative error:

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