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最大似然

于 2020-01-03 发布
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说明:  两种不同的假设: H1 : 0 xn A fn wn ( ) cos(2 ) ( ) = ++ π θ n=1,2,…,N,f0 为规一化频率 H0 : xn wn () () = n=1,2,…,N 其中 w[n]是均值为 0,方差为 2 σ n 的高斯白噪声,A 已知,样本间相互 独立,信号与噪声相互独立; 相位θ 是随机变量,它服从均匀分布 1 0 2 ( ) 20 p θ π θ π ?? ≤ ≤ = ??? 其它 1)改变输入信噪比(改变 A 或噪声方差均可),给定虚警概率,画出 输入信噪比与检测概率之间的理论曲线。(注意:理论检测曲线与样本 数有关) 2)改变样本数,用 Monte-Carlo 实验方法得出 PF=0.001 时输入信噪比 与检测概率之间关系曲线(至少三条),并得出结论。 3)改变 M-C 实验次数,样本数不变,用 Monte-Carlo 实验方法得出 PF =0.001 时输入信噪比与检测概率之间关系曲线(至少三条),并得出 结论(Draw the theoretical curve between input SNR and detection probability)

文件列表:

最大似然, 0 , 2020-01-03
最大似然\改变样本数取值实验程序.m, 3772 , 2019-12-14
最大似然\理论曲线以及改变蒙特卡洛实验次数程序.m, 3696 , 2019-12-14

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