Theory and Use of the Em Algorithm Contributor(s): Gupta, Maya R. (Author), Chen, Yihua (Author) |
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ISBN: 1601984308 ISBN-13: 9781601984302 Publisher: Now Publishers OUR PRICE: $61.75 Product Type: Paperback Published: March 2011 |
Additional Information |
BISAC Categories: - Technology & Engineering | Electronics - General - Technology & Engineering | Engineering (general) - Technology & Engineering | Signals & Signal Processing |
Dewey: 621.382 |
Series: Foundations and Trends(r) in Signal Processing |
Physical Information: 0.18" H x 6.14" W x 9.21" (0.30 lbs) 88 pages |
Descriptions, Reviews, Etc. |
Publisher Description: Theory and Use of the EM Algorithm introduces the expectation-maximization (EM) algorithm and provides an intuitive and mathematically rigorous understanding of this method. It describes in detail two of the most popular applications of EM: estimating Gaussian mixture models (GMMs), and estimating hidden Markov models (HMMs). It also covers the use of EM for learning an optimal mixture of fixed models, for estimating the parameters of a compound Dirichlet distribution, and for disentangling superimposed signals. It discusses problems that arise in practice with EM, and variants of the algorithm that help deal with these challenges. Theory and Use of the EM Algorithm is designed to be useful to both the EM novice and the experienced EM user looking to better understand the method and its use. |