4.1 Chapter highlights • Hypothesis testing and the MAP criterion • Extension to the general Bayes criterion • Minimax criterion • Neyman-Person criterion 4.2 Hypothesis testing & MAP criterion 4.3 Bayes criterion 4.4 Minimax criterion 4.5 Neyman-Pearson criterion

6.1 Chapter highlights • Composite hypothesis testing. • Unknown phase. • Unknown amplitude. • Unknown frequency. • Unknown time of arrival. 6.2 Composite hypothesis testing 6.3 Unknown phase 6.4 Unknown amplitude 6.5 Unknown frequency 6.6 Unknown time of arrival

11.1 Chapter highlights • Parameter estimation in WGN • Amplitude estimation in the coherent case • Amplitude estimation in the noncoherent case • Phase estimation in WGN • Time-delay estimation in WGN • Frequency estimation in WGN 11.2 Parameter estimation in WGN 11.4 Amplitude estimation in the coherent case with WGN 11.5 Amplitude estimation in the noncoherent case with WGN 11.6 Phase estimation in WGN 11.7 Time-delay estimation in WGN 11.8 Frequency estimation in WGN

10.1 Chapter highlights • Parameter estimation problem formulation • Properties of estimators • Bayes estimation • Minimax estimation • Maximum-likelihood estimation • Comparison of estimators of parameters 10.2 Formulation of the general parameter estimation problem 10.3 Types of estimation problems 10.5 Properties of estimators 10.6 Bayes estimation 10.7 Minimax estimation 10.8 Maximum-likelihood estimation

 1 线性相位FIR数字滤波器的特点  2 窗函数设计法  3 IIR与FIR数字滤波器的比较

周期序列的DFS及性质 离散傅里叶变换（DFT）及性质 DFT的快速算法（FFT） DFT/FFT的应用

5.5 The optimum digital detector in additive Gaussian noise 5.6 Filtering alternatives 5.7 Continuous signals - White Gaussian noise 5.8 Continuous signals - Colored Gaussian noise 5.9 Performance of binary receivers in AWGN 5.11 Sequential detection & performance

一、全通系统 二、最小相位系统 三、模拟低通滤波器设计 四、脉冲响应不变法 五、双线性变换法 六、模拟域频率变换

一、线性相位FIR滤波器的性质 二、窗函数法设计FIR滤波器 三、频率取样法设计线性相位FIR滤波器 四、线性相位FIR滤波器的优化设计

一、问题的提出 二、解决问题的思路与方法 三、基2时间抽取FFT算法 四、基2时间抽取FFT算法的计算复杂度 五、基2时间抽取FFT算法流图规律 六、基2频率抽取FFT算法 七、FFT算法的实际应用