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# Information Theory: A Tutorial Introduction

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Originally developed by Claude Shannon in the 1940s, the theory of information laid the foundations for the digital revolution, and is now an essential tool in deep space communication, genetics, linguistics, data compression, and brain sciences. In this richly illustrated book, accessible examples are used to show how information theory can be understood in terms of every
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Paperback, 243 pages

Published
February 1st 2015
by Sebtel Press

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*“Information is a fundamental physical quantity, obeying exact laws”*(Deutsch D and Mareletto C, 2014).

As very aptly stated in this book, information is a fundamental physical quantity, not substantially different in this regard to other "quantities" such as energy or mass, and it can justifiably be viewed as “nature's currency”. The misconceived old belief that information is just an abstract, purely theoretical construct devoid of physical reality and only applicable to specialist fields such ...more

What a great intro to a subject I found fascinating and is widely applicable: Digital communications, computing, neuro-science and other biological sciences, linguistics (a favourite) and then there's my secret application that made me want to read the book in the first place...but you won't find it in the book.

There is a proper glossary of technical terms, something that long term readers of my reviews know I think is essential and yet all too frequently absent. There are also ...more

The opening chapter 'What is information?' w ...more

rigour follows insight

A pleasure to spend time with. Stone's arguments are complete without being bloated, and he has a keen eye for philosophical and intuitive implications ("Why does maximum information look like pure noise?", "What exactly does half a bit mean?", and much more). This completeness means that he sometimes repeats definitions or lemmas, but I defy you to find this unhelpful.

The bibliography is also excellent, ranking a hundred books by their specialty and difficulty.

(Quibble ...more

The book is divided into chapters and further subdivided into sections. At the end of each section are Key Con ...more

As demonstrated in his other book(Bayes' Rule: A Tutorial Introduction to Bayesian Analysis), James spends a considerable amount of time to solidify reader's interest and explain minimally required knowledge prior to present any new concepts. On the bright side, this method covers a wide range of audiences, which could include one with ...more

**Fairly pedestrian**

A basic introduction to Shannon’s early results in information theory. The book does attempt to make clear how unexpected and revolutionary these results were. To us now ... how could it ever be expected to be otherwise.

However the long detailed explanations and long pages of repetitious equations are uninspired and I am sure not terribly illuminating if you don’t know it already. That’s the test. Can you explain it to someone who doesn’t know it. You have to teach it not just ...more

**Not bad, but not great.**

I have read more entertaining books on the subject. The author goes to great pains to illustrate the proofs and processes of determining entropy and information rates . Sometimes it seems highly repetitive. It may be that I just wasn’t following all of his arguments. Might be my fault not his.

Jan 03, 2020
Steve Hagen
added it

Good overview for the newcomer. Intuitive explanations, good examples, and not very technical. As a mathematical presentation of the subject it is surprisingly easy reading.

"Suppose we are given a coin, and we are told that it lands heads up 90% of the time. ... Whe ...more

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