◆理解数字滤波器的基本概念 ◆了解最小相位延时系统 ◆理解全通系统的特点及应用 ◆掌握冲激响应不变法 ◆掌握双线性变换法 ◆掌握 Butterworth、 Chebyshev低通滤波器的特点 ◆了解利用模拟滤波器设计IIR数字滤波器的设计过程 ◆了解利用频带变换法设计各种类型数字滤波器的方法

 S1. Introduction  S2. Conventional Kalman filter  S3. Example  S4. RLS and Kalman filtering  S5. Square-root information filter  S6. Square-root covariance filter  Better numerical properties than the conventional one  The square-root RLS algorithms are special cases

◆掌握线性相位FR数字滤波器的特点 ◆掌握窗函数设计法 ◆理解频率抽样设计法 ◆了解设计FIR滤波器的最优化方法 ◆理解IR与FIR数字滤波器的比较

 S.1 Prototype adaptive filter  Filter structure  Quadratic cost functions  S2. Wiener filter theory  MMSE criterion  Wiener-Hopf equations  Orthogonality principle  S3. Unrealizable Wiener filter

 Introduction  Periodogram and correlogram  Nonparametric methods  Parametric methods for Rational spectra  Parametric methods for line spectra  Filter-bank approach  Spatial methods

 S1. Filters: devices of signal processing  Classic Filter  Optimal Filter  Adaptive Filter  S2. Adaptive filtering applications  S3. Stochastic processes  Partial characteristic: Autocorrelation Matrix (ACM)  PSD  Linear parametric model  S4. Mean Square Information Space

◆8.0 Introduction ◆8.1 Representation of Periodic Sequence: the Discrete Fourier Series ◆8.2 Properties of the Discrete Fourier Series ◆8.3 The Fourier Transform of Periodic Signal ◆8.4 Sampling the Fourier Transform ◆8.5 Fourier Representation of Finite-Duration Sequence: the Discrete Fourier Transform ◆8.6 Properties of the Discrete Fourier Transform ◆8.7 Linear Convolution using the Discrete Fourier Transform ◆8.8 the discrete cosine transform (DCT)

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、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、DF按频率特性分类 可分为低通、高通、带通、带阻和全通,其特点为: (1)频率变量以数字频率O表示,=QT,Ω为模拟角频率,T为抽样时间间隔;