Aspects of information detection using entropy

Abstract

An evolving learning system should be able to self-organise on its input vector continuously through time. This paper presents initial simulation results which show that entropy is a measure which could be employed to find various coding structure information by inspection of a binary input channel through time. It also shows that source information needs to be sparsely coded for entropy to be able to detect which code bitstring lengths are being employed to communicate source information to a self-organizing system.<>