In the Viterbi algorithm, the negative log-likelihood estimates, accumulated distances, or path metrics are unboundedly increasing functions of time. For implementation, all variables must be confined to a finite range. The following properties of the Viterbi algorithm can be exploited for this purpose: (1) path selection depends only on differences of metrics; an (2) the difference between metrics is bounded. In the rescaling scheme, at each iteration the minimum metric is subtracted from all metrics. The use of two's complement arithmetic is proposed as an alternative to the rescaling method. This scheme avoids any kind of rescaling subtractions. Obvious advantages in implementation are hardware savings and a speedup inside the metric update loop, which is critical to the decoder's computational throughput. >