Fr. 266.00

Fundamentals of Signal Processing in Metric Spaces With Lattice - Algebraic Approach

Inglese · Copertina rigida

Spedizione di solito entro 1 a 3 settimane (non disponibile a breve termine)

Descrizione

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Sommario

General Ideas of Natural Science, Signal Theory, and Information Theory. Information Carrier Space Built upon Generalized Boolean Algebra with a Measure. Informational Characteristics and Properties of Stochastic Processes. Signal Spaces with Lattice Properties. Communication Channel Capacity. Quality Indices of Signal Processing in Metric Spaces with L-group Properties. Synthesis and Analysis of Signal Processing Algorithms.

Info autore

Andrey Popoff received a Specialist degree (an intermediate one between B.S. and M.S.) in electronic systems from Kiev Radioengineering Institute of Air Defence in 1985 (in Kiev, former USSR). He started his career as an officer of Electronic Intelligence Corps in the Central group of troops of USSR Armed Forces deployed in former Czechoslovakia (now Czech Republic).
A. Popoff received his Candidate of Science degree (Ph.D. equivalent) in electronic systems/defence technologies from Kiev Military Institute of Control and Communication in 1996. As an instructor at Kiev Military Institute of Control and Communication, and later as an assistant professor, associate professor, professor at National Academy (later renamed to National University) of Defence of Ukraine, A. Popoff worked in the fields of Electronic Warfare (EW), information theory, signal processing, radar and communication systems, and also led courses on the corresponding topics. At present, A. Popoff is a retired colonel and research professor of EW research laboratory at Central Research Institute of Armament and Defence Technologies, Kiev, Ukraine.

Riassunto

The book's focus is interrelation between information theory and signal processing theory. It explores the methodology of constructing the unified mathematical fundamentals of information theory and signal processing theory, the methods of synthesis of signal processing algorithms under prior uncertainty conditions, and evaluating their efficiency.

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