Overview

Information must be one of the most used words of today's world. Computers, media and the internet dominate many of our lives. The volume of information we collect and store increases annually, so much so that energy efficiency for data storage and manipulation is becoming a serious issue (Ranganathan, 2010). This omnipresence has given us everyday measures of information, bits, nips, nibbles, bytes, kilobytes, megabytes, gigabtyes terabytes, petabytes, exabytes … But what do these quantities really mean?

Entropy is effectively average information, and the quantity which defines the capacity of a transmission channel or storage medium. It is this second of the two fairly mathematical chapters addressing three interrelated concepts: information and entropy (§4.2, §4.2.1); noise (§4.4); and bandwidth, which links back to the previous chapter on Fourier Analysis. The emphasis is, again, on the concepts and how to visualise what happens rather than detailed physics and mathematics. Bialek (2002) gives a very detailed and thorough account of the mathematical framework.

Information has a companion concept, entropy (§4.2). Whereas anybody would offer you a definition of information, fewer would hazard a guess at entropy. Yet together they are amongst the most powerful of all concepts in science and engineering. In statistical mechanics, entropy is a measure of the disorder of a system and corresponds to the number of microstates a system can occupy. Without delving too deeply into the physics, which space does not permit, the relationship to computer systems can be explained fairly simply.