According to the limitation of the principle of outlier detection based on wavelet, this paper proposes an
outlier detection method called wavelet-hidden Markov model(W-HMM) algorithm. In this algorithm, the signal is
decomposed under some scale, and when the wavelet decompositions of the signal are different from the most other wavelet
decompositions, the signal can be seen as potential outlier. Aiming to make further accurate judgement, and by calculating the
similarity probability between the wavelet coefficient of this signal and that of normal signal, the final confirming is obtained
by using Viterbi algorithm which is applied to HMM. Finally, experimentation and application show the effectiveness and
practicality of the proposed detection method.