Ece437 Project Report Wavelet{domain Statistical Modeling Using Hmms
نویسنده
چکیده
Wavelet{based techniques has long been known in signal/image processing literature, and applied into various applications such as denoising and compression. As a separate framework, hidden Markov model (HMM) has been widely used to provide formal statistical models. This projects follows the paper by M. Crouse et al 1], trying to make the connection between these two separate concepts. The wavelet representation of a signal often has the properties of clustering and persistence across scales. By investigating these properties we develop a wavelet{domain HMM to model the wavelet coeecients. An eecient Expectation Maximization (EM) algorithm is developed for tting the HMMs to observational wavelet coeecients. After the model is obtained, we can use this model into the framework of signal estimation, and many other applications as well.
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