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Information Measures
Rok: 2001
ISBN: 9783540416333
OKCZID: 110095060
Citace (dle ČSN ISO 690):
ARNDT, C. Information measures: information and its description in science and engineering. Berlin: Springer, c2001. xix, 547 s.
Anotace
This book is an introduction to the mathematical description of information in science and engineering. The necessary ma- thematical theory will be treated in a more vivid way than in the usual theoretical proof structure. This enables the reader to develop an idea of the connections between diffe- rent information measures and to understand the trains of thoughts in their derivation. As there exist a great number of different possible ways to describe information, these measures are presented in a coherent manner. Some examples of the information measures examined are: Shannon informati- on, applied in coding theory; Akaike information criterion, used in system identification to determine auto-regressive models and in neural networks to identify the number of neu- rons; and Cramer-Rao bound or Fisher information, describing the minimal variances achieved by unbiased estimators. From the reviews: "Bioinformaticians are facing the challenge of how to handle immense amounts of raw data, such as are generated from genome mapping, make sense of them, and render them accessible to scientists working on a wide variety of problems. "Information Measures: Information and its Description in Science and Engineering" can be such a tool." - IEEE Engineering in Medicine and Biology MATHEMATICAL REVIEWS "A distinction of this book from the earlier books is that the mathematical theory is treated in a more vivid way than in the usual theorem-proof structure. This enables the author to develop an idea of the connections between different information measures and to indicate the trains of thought in their derivation, which are important for applications...it contains some ideas on description of information which are helpful to users...It can be used as a reference book or a handbook for researchers, engineers, and graduate students in related specialties who are interested in applying information measures to their problems."