Presents a definition of information loss for signal processing systems which is the basis of an information-theoretic systems theory
Analyzes various systems in the signal processing engineer's toolbox: polynomials, quantizers, rectifiers, linear filters with and without quantization effects, principal components analysis, multirate systems, etc.
Highlights differences and similarities between design principles based on information-theoretic quantities and those based on energetic measures, such as the mean-squared error

Inhalt
Introduction.- Part I: Random Variables.- Piecewise Bijective Functions and Continuous Inputs.- General Input Distributions.- Dimensionality-Reducing Functions.- Relevant Information Loss.- II. Part II: Stationary Stochastic Processes.- Discrete-Valued Processes.- Piecewise Bijective Functions and Continuous Inputs.- Dimensionality-Reducing Functions.- Relevant Information Loss Rate.- Conclusion and Outlook.