|
(3.1) |
where H(P) is the Shannon's entropy given by (1.7).
Campbell (1965) [20] for the first time, has shown that the variable lenght version of the elementary coding theorem carries over to the entropy of order , if one considers exponential lenght and its increasing functions, which includes, in particular, a generalized lenght in terms of entropy of order. Blumer and McEliece (1988) [14] considered the problem of minimizing redundancy of order defined in terms of entropy of order , and obtained bounds sharper than that of Gallager (1978) [39]. Taneja (1984a) [101] extended the concept of exponentiated average codeword lenght of order to the best 1:1 codes. For some other aplications of entropy of order refer to Jelinek (1968a;b) [50] [51], Jelinek and Schneider (1972) [52], Csiszár (1974) [29], Nath (1975) [74], Arimoto (1975; 1976) [4], [5], Ben-Bassat and Raviv (1978) [11], Kieffer (1979) [64], Campbell (1985) [22], Kapur (1983; 1986) [55], [56] etc..
Based on the same motivations of Rényi, later researchers (Aczél and Daróczy, 1963 [1]; Varma, 1966 [119]; Kapur, 1967 [54]; Rathie, 1970 [78], etc..) generalized the entropy of order by changing some of its postulates. The generaliation studied by Aczél and Daróczy (1963) [1], known as entropy of order is given by
|
(3.2) |
for all , where and are real parameters. In particular, when or , the measure (3.2) reduces to (3.1). We can easily verify that
that reduces to Shannon's entropy for.