Generalized measures of useful R norm information and mean codeword lengths

Abstract

As our perception of the world becomes increasingly complex the number of phenomena about which we are uncertain increases and uncertainty about each phenomenon can also increase To decrease this uncertainty we collect an ever increasing amount of information Uncertainty is not a single meaning concept It can appear in several guises for example there may be uncertainty to win an election that which brand of product will have the maximum share of the market What grade a student will get The real birth of information theory could be traced about 66 years back with the publication of the first seminal paper on A Mathematical Theory of Communication by Claude Shannon1948 in Bell System Technical Journal In this paper Shannon gave a quantitative measure of entropy associated with a probability distribution and showed its connection with the coding theory Thereafter the mathematician Wiener 1949 took interest in the importance of communication theory In the sequential years Shannon studied many applications in various fields such as physics urban and regional planning marketing spectral analysis computerized tomography economics etc This measure was also interpreted as a measure of equality and was used as such as in linguistics Psychology and other areas