离散信号的滤波

第1章  离散随机信号                  
 1.1  随机变量及统计特性                  
 1.2  正交投影原理                  
 1.3  离散随机信号                  
 1.4  随机序列经过线性滤波器                  
 1.5  最小相位滤波器                  
 1.6  信号模型                  
 1.7  随机变量的参数估计                  
 第2章  Wiener滤波                  
 2.1  信号的滤波                  
 2.2  Wiener-Hoff方程                  
 2.3  平稳序列的Wiener滤波                  
 2.4  平稳序列的Wiener预测                  
 2.5  Levinson-Durbin算法                  
 2.6  格型滤波器                  
 2.7  Burg算法                  
 2.8  功率谱估计                  
 第3章  Kalman滤波                  
 3.1  状态与观测方程                  
 3.2  Kalman滤波                  
 3.3  有色噪声模型的Kalman滤波                  
 第4章  自适应滤波                  
 4.1  FIR Weiner滤波器                  
 4.2  LMS自适应算法                  
 4.3  步长因子 m 的取值范围                  
 4.4  学习曲线                  
 4.5  失调                  
 4.6  RLS自适应滤波                  
 4.7  自适应噪声抵消                  
 4.8  自适应信道均衡器                  
 第5章  小波滤波                  
 5.1  连续小波变换                  
 5.2  二进小波变换                  
 5.3  离散二进小波变换                  
 5.4  Daubechies小波                  
 5.5  双正交小波变换                  
 5.6  信号的最大模重建                  
 5.7  利用最大模重建滤除噪声                  
 5.8  软门限去噪                  
 第6章  同态滤波                  
 6.1  同态滤波的定义                  
 6.2  解相乘同态系统                  
 6.3  解卷积同态系统                  
 6.4  复时谱的计算                  
 6.5  指数序列的复时谱                  
 第7章  中值滤波                  
 7.1  中值滤波的定义                  
 7.2  中值滤波的门限分解算法                  
 7.3  中值滤波的输出统计特性                  
 7.4  多级中值滤波                  
 7.5  序统计滤波                  
 7.6  近均值滤波                  
 7.7  Lee滤波                  
 7.8  梯度倒数加权滤波                  
 第8章  形态滤波                  
 8.1  形态学的基本运算和性质                  
 8.2  Matheron表示定理                  
 8.3  一维信号的形态滤波                  
 8.4  一维形态滤波的输出统计特性                  
 参考文献