Titlebook: Information Systems and Data Compression; Jerzy A. Seidler Book 1997 Springer Science+Business Media New York 1997 communication.communica

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https://doi.org/10.1007/b102306communication; communication system; communication systems; data compression; design; information system;

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Basic Functions and Structures of Information Systemsrmits a uniform treatment of systems for information acquisition, transmission, storage, and compression, for feature extraction, and for the execution of given algorithms. The concepts introduced in this chapter are illustrated with typical examples of information systems presented in the next chapter.

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Dimensionality Reduction and Quantizationinformation processing is efficient and cheap. Section 1.5.4 described the basic transformations of the primary continuous information into discrete information. Such a transformation is called .; discretization of scalar or vector information is called... The important types of discretization are listed in Figure 1.22.

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Structures and Features of Optimal Information Systemsncrete optimization problems. They now serve as examples of general methods that are presented here. On the other hand, considerations in this chapter show those specific problems in a broader perspective and provide formal justifications for the heuristic assumption that have been introduced previously.

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Examples of Information SystemsThe first purpose of this chapter is to illustrate on concrete examples the general concepts introduced in Chapter 1 and to show that they allow a uniform treatment of a great variety of information systems.

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ork for information concepts is introduced forvarious types of information systems such as communication systems,information storage systems and systems for simplifying structuredinformation. The book introduces several new concepts and presents anovel interpretation of a wide range of topics in com

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Lossless Compression of Informatione understand it intuitively as a preliminary transformation of structured information that allows to reduce the resources necessary for subsequent processing of the information. An introduction to the problems of information compression has been presented in Section 1.5.4; see in particular, Figure 1.22.