Source matching problems revisited
C.-I. Chang, L. Wolfe · IEEE Transactions on Information Theory · 1992
The source matching problem is to find the minimax codes that minimize the maximum redundancies over classes of sources where relative entropy (cross entropy, discrimination information) is adopted as a criterion to measure the redundancy. The convergence of a simple approach different from L.D. Davisson and A. Leon-Garcia's (1980) algorithm for finding such minimax codes is presented and shown. This approach is applied as an example to the class of first-order discrete Markov sources. The sufficient statistic previously used by D.H. Lee (1983) in his attempt to produce results for the first-order Markov source matching problem is corrected. A computational complexity analysis and a numerical study further demonstrate that this simple algorithm significantly reduces the required computing time, when compared to Davisson and Leon-Garcia's algorithm.>