A Markovian technique is described to calculate the exact performance of the Viterbi algorithm used as either a channel decoder or a source encoder for a convolutional code. The probability of information bit error and the expected Hamming distortion are computed for codes of various rates and constraint lengths. The concept of tie-breaking rules is introduced and its influence on decoder performance is examined. Computer simulation is used to verify the accuracy of the results. Finally, we discuss the issue of when a coded system outperforms an uncoded system in light of the new results.>

The main lines of a partial proof of the "perfect code theorem" are presented. The relevant part refers to the nonexistence of unknownt-perfect codes over arbitrary alphabets fort \not \in \{1, 2, 6, 8\}. The details of the proof can be found in the author's Ph.D. dissertation at the University of Amsterdam.

Improved bounds forA(n,d), the maximum number of codewords in a (linear or nonlinear) binary code of word lengthnand minimum distanced, and forA(n,d,w), the maximum number of binary vectors of lengthn, distanced, and constant weightwin the rangen \leq 24andd \leq 10are presented. Some of the new values areA