Chapter 12 continues the discussion on prediction filtering and identification. Infinite memory linear predictors and Wiener filters are derived using the mean squared formulation. The basic elements of the Kolmogorov-Wiener theory are highlighted. Digital Pulse Amplitude modulation and demodulation are introduced. An alternative approach to filtering is offered by the Kalman filter.
Identification is discussed in the context of convolutional and finite difference models.
Topics include blind identification, instrumental variables, nonlinear regressions and the prediction error algorithm. Finally, second order Volterra system identification is discussed. Three major control system design methods are presented in Chapter 13, the transform design approach relying on the transfer function description of systems, the Pole placement design using state space ideas and the regulator design based on quadratic function minimization. Chapter 14 deals with compression and error control coding. Popular compression techniques such as transform coding and the discrete cosine transform are presented.