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Asymmetry: The Foundation of Information

by Scott J. Muller
Save 35% Save 35%
Current price ₹3,672.00
Original price ₹5,649.00
Original price ₹5,649.00
Original price ₹5,649.00
(-35%)
₹3,672.00
Current price ₹3,672.00

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Book cover type: Paperback
  • ISBN13: 9783642089329
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Springer
  • Publisher Imprint: Springer
  • Publication Date:
  • Pages: 165
  • Original Price: EUR 49.99
  • Language: English
  • Edition: N/A
  • Item Weight: 275 grams
  • BISAC Subject(s): Information Theory, Group Theory, and Applied

From the Back Cover

As individual needs have arisen in the fields of physics, electrical engineering and computational science, each has created its own theories of information to serve as conceptual instruments for advancing developments. This book provides a coherent consolidation of information theories from these different fields. The author gives a survey of current theories and then introduces the underlying notion of symmetry, showing how information is related to the capacity of a system to distinguish itself. A formal methodology using group theory is employed and leads to the application of Burnside's Lemma to count distinguishable states. This provides a versatile tool for quantifying complexity and information capacity in any physical system. Written in an informal style, the book is accessible to all researchers in the fields of physics, chemistry, biology, computational science as well as many others.

Scott Muller graduated from the University of Queensland in Chemical Engineering specialising in biotechnology. He worked in Australia and Italy in the biotechnology and pharmaceutical industries. In 2004 he received his doctorate from the University of Newcastle (Australia) where he studied the foundations of information and conducted research into the nature of "emergence". Recently he has worked on automated reasoning and expert systems in the telecommunications industry. Scott is currently developing industrial, adaptive decision-making systems using evolutionary programming techniques.

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