The Mathematical Theory of Information (The Springer International Series in Engineering and Computer Science)

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9781461353324: The Mathematical Theory of Information (The Springer International Series in Engineering and Computer Science)

The general concept of information is here, for the first time, defined mathematically by adding one single axiom to the probability theory. This Mathematical Theory of Information is explored in fourteen chapters: 1. Information can be measured in different units, in anything from bits to dollars. We will here argue that any measure is acceptable if it does not violate the Law of Diminishing Information. This law is supported by two independent arguments: one derived from the Bar-Hillel ideal receiver, the other is based on Shannon's noisy channel. The entropy in the 'classical information theory' is one of the measures conforming to the Law of Diminishing Information, but it has, however, properties such as being symmetric, which makes it unsuitable for some applications. The measure reliability is found to be a universal information measure. 2. For discrete and finite signals, the Law of Diminishing Information is defined mathematically, using probability theory and matrix algebra. 3. The Law of Diminishing Information is used as an axiom to derive essential properties of information. Byron's law: there is more information in a lie than in gibberish. Preservation: no information is lost in a reversible channel. Etc. The Mathematical Theory of Information supports colligation, i. e. the property to bind facts together making 'two plus two greater than four'. Colligation is a must when the information carries knowledge, or is a base for decisions. In such cases, reliability is always a useful information measure. Entropy does not allow colligation.

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The Mathematical Theory of Information presents a new mathematical theory of information, built on a single powerful postulate: the Law of Diminishing Information. The concept of information is here, for the first time, defined mathematically by adding this postulate to the axioms of the probability theory. The Law of Diminishing Information is founded on a fusion of two fundamental ideas: Carnap and Bar-Hillel's `Ideal Receiver' and Shannon's `Noisy Channel'.

The Law of Diminishing Information is applied to information technology, game theory, legislation, logic of research, algorithmic information, chaos theory, control engineering, medical tests, and biological evolution. In physics, both the Second Law of Thermodynamics and Schrödinger's wave function are derived from the Law of Diminishing Information. Conventional information theory, that of telecommunications, is analyzed as a special case, and eight conditions for its applicability are listed.

The reader will get the essential ideas to understand and use the concept of information. The Mathematical Theory of Information is suitable as a textbook in general information theory for students of technical, scientific, and mathematical subjects. The book is ideal as a supplementary textbook in traditional courses on telecommunications information theory at all levels.

The website of the book is www.matheory.info.

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Book Description Springer-Verlag New York Inc., United States, 2013. Paperback. Book Condition: New. 235 x 155 mm. Language: English Brand New Book ***** Print on Demand *****.The general concept of information is here, for the first time, defined mathematically by adding one single axiom to the probability theory. This Mathematical Theory of Information is explored in fourteen chapters: 1. Information can be measured in different units, in anything from bits to dollars. We will here argue that any measure is acceptable if it does not violate the Law of Diminishing Information. This law is supported by two independent arguments: one derived from the Bar-Hillel ideal receiver, the other is based on Shannon s noisy channel. The entropy in the classical information theory is one of the measures conforming to the Law of Diminishing Information, but it has, however, properties such as being symmetric, which makes it unsuitable for some applications. The measure reliability is found to be a universal information measure. 2. For discrete and finite signals, the Law of Diminishing Information is defined mathematically, using probability theory and matrix algebra. 3. The Law of Diminishing Information is used as an axiom to derive essential properties of information. Byron s law: there is more information in a lie than in gibberish. Preservation: no information is lost in a reversible channel. Etc. The Mathematical Theory of Information supports colligation, i. e. the property to bind facts together making two plus two greater than four . Colligation is a must when the information carries knowledge, or is a base for decisions. In such cases, reliability is always a useful information measure. Entropy does not allow colligation. Softcover reprint of the original 1st ed. 2002. Bookseller Inventory # AAV9781461353324

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Book Description Springer-Verlag New York Inc., United States, 2013. Paperback. Book Condition: New. 235 x 155 mm. Language: English . Brand New Book ***** Print on Demand *****. The general concept of information is here, for the first time, defined mathematically by adding one single axiom to the probability theory. This Mathematical Theory of Information is explored in fourteen chapters: 1. Information can be measured in different units, in anything from bits to dollars. We will here argue that any measure is acceptable if it does not violate the Law of Diminishing Information. This law is supported by two independent arguments: one derived from the Bar-Hillel ideal receiver, the other is based on Shannon s noisy channel. The entropy in the classical information theory is one of the measures conforming to the Law of Diminishing Information, but it has, however, properties such as being symmetric, which makes it unsuitable for some applications. The measure reliability is found to be a universal information measure. 2. For discrete and finite signals, the Law of Diminishing Information is defined mathematically, using probability theory and matrix algebra. 3. The Law of Diminishing Information is used as an axiom to derive essential properties of information. Byron s law: there is more information in a lie than in gibberish. Preservation: no information is lost in a reversible channel. Etc. The Mathematical Theory of Information supports colligation, i. e. the property to bind facts together making two plus two greater than four . Colligation is a must when the information carries knowledge, or is a base for decisions. In such cases, reliability is always a useful information measure. Entropy does not allow colligation. Softcover reprint of the original 1st ed. 2002. Bookseller Inventory # AAV9781461353324

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Book Description Springer. Paperback. Book Condition: New. Paperback. 502 pages. Dimensions: 9.2in. x 6.1in. x 1.2in.The general concept of information is here, for the first time, defined mathematically by adding one single axiom to the probability theory. This Mathematical Theory of Information is explored in fourteen chapters: 1. Information can be measured in different units, in anything from bits to dollars. We will here argue that any measure is acceptable if it does not violate the Law of Diminishing Information. This law is supported by two independent arguments: one derived from the Bar-Hillel ideal receiver, the other is based on Shannons noisy channel. The entropy in the classical information theory is one of the measures conforming to the Law of Diminishing Information, but it has, however, properties such as being symmetric, which makes it unsuitable for some applications. The measure reliability is found to be a universal information measure. 2. For discrete and finite signals, the Law of Diminishing Information is defined mathematically, using probability theory and matrix algebra. 3. The Law of Diminishing Information is used as an axiom to derive essential properties of information. Byrons law: there is more information in a lie than in gibberish. Preservation: no information is lost in a reversible channel. Etc. The Mathematical Theory of Information supports colligation, i. e. the property to bind facts together making two plus two greater than four. Colligation is a must when the information carries knowledge, or is a base for decisions. In such cases, reliability is always a useful information measure. Entropy does not allow colligation. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Paperback. Bookseller Inventory # 9781461353324

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