9781402074653 - variation principle in informational macrodynamics (the springer international series in engineering and computer science, band 736) von lerner, vladimir s. (4 Ergebnisse)
Sprache: Englisch
Verlag: Springer 2003
Serie: The Springer International Series in Engineering and Computer Science, Buch 180 von 260. Buch 180 von 260 - The Springer International Series in Engineering and Computer Science
- Hardcover
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Zustand: New. In.
Sprache: Englisch
Verlag: Kluwer Academic Publishers 2003
Serie: The Springer International Series in Engineering and Computer Science, Buch 180 von 260. Buch 180 von 260 - The Springer International Series in Engineering and Computer Science
- Hardcover
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Zustand: New. Introduces the process' integral information measure, which has a distinctive difference from information approaches that use an entropy function. The mathematical formalisms and methods, implemented in the forms of computer models, algorithms and programs, provide tools for Information Systems' Modeling. Series: T…he Springer International Series in Engineering and Computer Science. Num Pages: 266 pages, biography. BIC Classification: GPJ; URY. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College); (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 234 x 156 x 17. Weight in Grams: 576. . 2003. Hardback. . . . . Books ship from the US and Ireland.
Sprache: Englisch
Verlag: Springer US 2003
Serie: The Springer International Series in Engineering and Computer Science, Buch 180 von 260. Buch 180 von 260 - The Springer International Series in Engineering and Computer Science
- Hardcover
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Zustand: New. Information Macrodynamics (IMD) belong to an interdisciplinary science that represents a new theoretical and computer-based methodology for a system informational descriptionand improvement,including various activities in such areas as thinking, intelligent.
Sprache: Englisch
Verlag: Springer Us Mai 2003 2003
Serie: The Springer International Series in Engineering and Computer Science, Buch 180 von 260. Buch 180 von 260 - The Springer International Series in Engineering and Computer Science
- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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Buch. Zustand: Neu. Neuware - Information Macrodynamics (IMD) belong to an interdisciplinary science that represents a new theoretical and computer-based methodology for a system informational descriptionand improvement,including various activities in such areas as thinking, intelligent processes, communications, management, and… other nonphysical subjects with their mutual interactions, informational superimposition, and theinformation transferredbetweeninteractions. The IMD is based on the implementation of a single concept by a unique mathematical principle and formalism, rather than on an artificial combination of many arbitrary, auxiliary concepts and/or postulates and different mathematical subjects, such as the game, automata, catastrophe, logical operations theories, etc. This concept is explored mathematically using classical mathematics as calculus of variation and the probability theory, which are potent enough, without needing to developnew,specifiedmathematical systemicmethods. The formal IMD model automatically includes the related results from other fields, such as linear, nonlinear, collective and chaotic dynamics, stability theory, theory of information, physical analogies of classical and quantum mechanics, irreversible thermodynamics, andkinetics. The main IMD goal is to reveal the information regularities, mathematically expressed by the considered variation principle (VP), as a mathematical tool to extractthe regularities and define the model, whichdescribes theregularities. The IMD regularities and mechanisms are the results of the analytical solutions and are not retained by logical argumentation, rational introduction, and a reasonable discussion. The IMD's information computer modeling formalism includes a human being (as an observer, carrier and producer ofinformation), witha restoration of the model during the objectobservations.
