Most probable path using Viterbi algorithm

The script provided decodes a set of observations to find the corresponding hidden states of a hmm.

Description

The submission considers a case where you deduce what weather it is given the status of a shirt that is hung outside. The weather could be Sunny, cloudy, Rainy and the shirt could be dry, dryish, damp etc. Now given some probability matrices (The initial probability of the weather, the transition probability of the weather and the observation given weather matrices), can the chain of weather be deduced?

The Viterbi algorithm is used to decode the states. So my submission does that job. The example may be changed to incorporate a variety of problems that can be modelled by HMM(Hidden Markov Models).

• MATLAB release: MATLAB 7.4 (R2007a)