§7.2 Selection of Filter Type §7.3 Digital Filter Design: Basic Approaches §7.4 IIR Digital Filter Design: Bilinear Transformation Method §7.5 Low pass FIR filter design §7.6 Fixed Window Functions §7.7 Design Steps for Windowed Low Pass FIR Filters

§2.1 Discrete-Time Signals: Time-Domain Representation §2.2 Operations on Sequences §2.3 Basic Sequences §2.4 The Sampling Process §2.5 Discrete-Time Systems §2.6 Time-Domain Characterization of LTI Discrete-Time System §2.7 Classification of LTI Discrete-Time Systems §2.8 Correlation of Signals

§4.1 LTI Discrete-Time Systems in the Transform Domain §4.2 The Frequency Response §4.3 Frequency Response Computation Using MATLAB §4.4 The Concept of Filtering §4.5 Phase and Group Delays §4.6 Frequency Response of the LTI Discrete-Time System §4.7 The Transfer Function §4.8 The Transfer Function §4.9 Frequency Response from Transfer Function §4.10 Types of Transfer Functions §4.11 Linear-Phase FIR Transfer Functions §4.12 Allpass Transfer Function §4.13 Minimum-Phase and Maximum-Phase Transfer Functions

§5.1 Digital Processing of Continuous-Time Signals §5.2 Sampling of Continuous-time Signals §5.3 Effect of Sampling in the Frequency Domain §5.4 Recovery of the Analog Signal §5.5 Implication of the Sampling Process §5.6 Sampling of Bandpass Signals §5.7 Analog Lowpass Filter Specifications §5.8 Analog Lowpass Filter Design

 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

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

 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

 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

§7.1 Digital Filter Specifications §7.2 Selection of Filter Type §7.3 Digital Filter Design: Basic Approaches §7.4 IIR Digital Filter Design: Bilinear Transformation Method §7.5 IIR Highpass, Bandpass, and Bandstop Digital Filter Design §7.6 Fixed Window Functions §7.7 FIR Filter Design Example

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