Offers a very thorough treatment of the

z-transform and frequency-domain analysis.

Beginning with deterministic signals and filters then moving to stochastic ones, he explores such topics as discrete time signals and systems, the

Z-transform, discrete filter design techniques, stochastic processes, and adaptive filters.

The design of these filters is based on the

z-transform.

Following the well-known approach developed by Stephenson and Mitalas (Stephenson and Mitalas 1971), based on the use of the

Z-transform (ZT) (Jury 1964), let us consider a thermal system, like a wall, in which u([tau]) is the input signal and y([tau]) is the correlated output signal.

The

z-transform is also covered, along with Hilbert transforms, for which a basic knowledge of complex variable theory is necessary.

The following analysis of the RiemannZeta function with a

z-transform shows the stability zones and requirements for the real and complex variables.

Key words: Logarithmic mean, Identric mean,

Z-transform and convolution.

Chapter 3 is devoted to transform-domain representations of discrete-time signals, specifically the DTFT, DFT and

Z-Transform, together with their properties and applications.

The

z-transform has also been used in several works [6-8].

Includes answers to selected exercises and an appendix with a useful table on Laplace and

z-transform pairs.

Part 1: Basic Digital Signal Processing gives an introduction to the topic, discussing sampling and quantization, Fourier analysis and synthesis,

Z-transform, and digital filters.

He also explores discrete time signals and systems, the

z-transform, continuous- and discrete-time filters, active and passive filters, lattice filters, continuous- and discrete-time state space models, and more.