Synopses & Reviews
This book is an introduction to the mathematical description of information in science and engineering. The necessary mathematical theory will be treated in a more vivid way than in the usual theorem-proof structure. This enables the reader to develop an idea of the connections between different 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 information, 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. This softcover edition addresses researchers and students in electrical engineering, particularly in control and communications, physics, and applied mathematics.
Review
"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
Synopsis
From the reviews: "Bioinformaticians are facing the challenge of how to handle immense amounts of raw data, [...] and render them accessible to scientists working on a wide variety of problems. [This book] can be such a tool." IEEE Engineering in Medicine and Biology
Synopsis
In recent decades, Western nations have increasingly implemented encompassing welfare state reforms that try to establish equality through social programs and governmental intervention rather than direct redistribution of funds. In this book, Christoph Arndt examines the political ramifications of reforming deeply entrenched welfare states through a careful comparative analysis of four European countries that recalibrated their system of social protection under social democratic governments. and#160;Arndt discovers that the andquot;third wayandquot; has produced a setback for social democrats and that the nature and scale of this setback is contingent on each countryandrsquo;s electoral system.
About the Author
Christoph Arndt is assistant professor in the Department of Political Science and Government, Aarhus University, Denmark.
Table of Contents
Abstract.- Introduction.- Basic considerations.- Historic development of information theory.- The concept of entropy in physics.- Extension of Shannon's information.- Generalized entropy measures.- Information functions and gaussian distributions.- Shannon's information of discrete distributions.- Information functions for gaussian distributions part II.- Bounds of the variance.- Ambiguity function.- Akaike's information criterion.- Channel information.- Deterministic and stochastic information.- Maximum entropy estimation.- Concluding remarks.- Appendix.- Bibliography.