**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

**Algorithmic Information Theory**

by

**Peter D. Gruenwald, Paul M.B. Vitanyi**-

**CWI**

We introduce algorithmic information theory, also known as the theory of Kolmogorov complexity. We explain this quantitative approach to defining information and discuss the extent to which Kolmogorov's and Shannon's theory have a common purpose.

(

**4866**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.

(

**13200**views)

**Entropy and Information Theory**

by

**Robert M. Gray**-

**Springer**

The book covers the theory of probabilistic information measures and application to coding theorems for information sources and noisy channels. This is an up-to-date treatment of traditional information theory emphasizing ergodic theory.

(

**10644**views)

**Quantum Information Theory**

by

**Renato Renner**-

**ETH Zurich**

Processing of information is necessarily a physical process. It is not surprising that physics and the theory of information are inherently connected. Quantum information theory is a research area whose goal is to explore this connection.

(

**6053**views)