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
A Short Course in Information Theoryby 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.
(15647 views)
Quantum Information Theoryby 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.
(14930 views)
Algorithmic Information Theoryby 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.
(12613 views)
Lecture Notes on Network Information Theoryby Abbas El Gamal, Young-Han Kim - arXiv
Network information theory deals with the fundamental limits on information flow in networks and optimal coding and protocols. These notes provide a broad coverage of key results, techniques, and open problems in network information theory.
(16926 views)