**A primer on information theory, with applications to neuroscience**

by Felix Effenberger

**Publisher**: arXiv 2013**Number of pages**: 58

**Description**:

This chapter is supposed to give a short introduction to the fundamentals of information theory; not only, but especially suited for people having a less firm background in mathematics and probability theory. Regarding applications, the focus will be on neuroscientific topics.

Download or read it online for free here:

**Download link**

(1MB, PDF)

## Similar books

**Quantum Information Theory**

by

**Robert H. Schumann**-

**arXiv**

A short review of ideas in quantum information theory. Quantum mechanics is presented together with some useful tools for quantum mechanics of open systems. The treatment is pedagogical and suitable for beginning graduates in the field.

(

**12263**views)

**Information Theory, Inference, and Learning Algorithms**

by

**David J. C. MacKay**-

**Cambridge University Press**

A textbook on information theory, Bayesian inference and learning algorithms, useful for undergraduates and postgraduates students, and as a reference for researchers. Essential reading for students of electrical engineering and computer science.

(

**22420**views)

**The Limits of Mathematics**

by

**Gregory J. Chaitin**-

**Springer**

The final version of a course on algorithmic information theory and the epistemology of mathematics. The book discusses the nature of mathematics in the light of information theory, and sustains the thesis that mathematics is quasi-empirical.

(

**8491**views)

**A Short Course in Information Theory**

by

**David J. C. MacKay**-

**University of Cambridge**

This text discusses the theorems of Claude Shannon, starting from the source coding theorem, and culminating in the noisy channel coding theorem. Along the way we will study simple examples of codes for data compression and error correction.

(

**9343**views)