We discuss minimum distance decoding of convolutional codes. The relev
ant distance functions are defined, and the set of correctable error p
atterns is described by a sequence of weight constraints. Decoding met
hods for error patterns of bounded weight are described, and it is dem
onstrated that these methods offer a favorable combination of performa
nce and complexity. Exact values and upper bounds on the error probabi
lity are calculated from finite state models of the decoding process.