Computationally Optimal Metric-First Code Tree Search Algorithms

Code tree search algorithms find wide applicability in source encoding, channel decoding, pattern recognition, and maximum likelihood sequence estimation. These algorithms search code trees and may be classified as depth-first, breadth-first, and metric-first depending on the search criterion employed. We define here a criterion for metric-first algorithms to be optimal. We show that implementations of metric-first searches proposed heretofore are not optimal, and we propose and analyze two algorithms which are. Experimental data obtained by encoding a voiced speech sound point to superiority of the proposed implementation over earlier versions.