This volume explores the interface between two diverse areas of applied mathematics which are both 'customers' of the maximum likelihood methodology; emission tomography and hidden Markov models as an approach to speech understanding. Other areas where maximum likelihood is used in this volume include parsing of text (Jelinek), microstructure of materials (Ji), DNA sequencing (Nelson). Most of the participants were in the main areas of speech or emission density reconstruction.
|Publisher:||Springer New York|
|Series:||IMA Volumes in Mathematics and its Applications Series , #80|
|Product dimensions:||6.14(w) x 9.21(h) x 0.24(d)|
Table of Contents
Contents: Iterative reconstruction algorithms based on cross-entropy minimization.- Stop consonants discrimination and clustering using nonlinear transformations and wavelets.- Maximum a posteriori image reconstructions from projections.- Direct parsing of text.- Hierarchical modelling for microstructure of certain brittle materials.- Hidden Markov Models estimation via the most informative stopping times for Vitervi algorithm.- Constrained shastic language models.- Recovering DNA sequences from electrophoresis data.- Image and speech and EM.- Non-stationary hidden Markov models for speech recognition.- Applications of the EM algorithm to linear inverse problems with positivity constraints.