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Hidden Markov processes : (Record no. 420196)

MARC details
000 -LEADER
fixed length control field 04347cam a2200253 i 4500
001 - CONTROL NUMBER
control field 136637
003 - CONTROL NUMBER IDENTIFIER
control field ISI Library, Kolkata
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20160314154727.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 140325t20142014njua b 001 0 eng
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780691133157 (hardcover : acidfree paper)
040 ## - CATALOGING SOURCE
Original cataloging agency ISI Library
Language of cataloging eng
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 570.285
Edition number 23
Item number V655
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Vidyasagar, M.
245 10 - TITLE STATEMENT
Title Hidden Markov processes :
Remainder of title theory and applications to biology /
Statement of responsibility, etc M. Vidyasagar.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Princeton :
Name of publisher, distributor, etc Princeton University Press,
Date of publication, distribution, etc c2014.
300 ## - PHYSICAL DESCRIPTION
Extent xiv, 287 p. :
Other physical details illustrations;
Dimensions 24 cm.
490 0# - SERIES STATEMENT
Series statement Princeton series in applied mathematics
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references and index.
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 1. Introduction to probability and random variables : Introduction to random variables ; Motivation ; Definition of a random variable and probability ; Function of a random variable, expected value ; Total variation distance ; Multiple random variables ; Joint and marginal distributions ; Independence and conditional distributions ; Bayes' rule ; MAP and maximum likelihood estimates ; Random variables assuming infinitely many values ; Some preliminaries ; Markov and Chebycheff inequalities ; Hoeffding's inequality ; Monte Carlo simulation ; Introduction to Cramer's theorem --<br/> 2. Introduction information theory : Convex and concave functions ; Entropy ; Definition of entropy ; Properties of the entropy function ; Conditional entropy ; Uniqueness of the entropy function ; Relative entropy and the Kullback-Leibler divergence --<br/> 3. Nonnegative matrices : Canonical form for nonnegative matrices ; Basic version of the canonical form ; Irreducible matrices ; Final version of canonical form ; Irreducibility, aperiodicity, and primitivity ; Canonical form for periodic irreducible matrices ; Perron-Frobenius theory ; Perron-Frobenius theorem for primitive matrices ; Perron-Frobenius theorem for irreducible matrices. <br/>4. Markov processes : Basic definitions ; The Markov property and the state transition matrix ; Estimating the state transition matrix ; Dynamics of stationary Markov chains ; Recurrent and transient states; Hitting probabilities and mean hitting times ; Ergodicity of Markov chains --<br/> 5. Introduction to large deviation theory : Problem formulation ; large deviation property for I.I.D. samples: Sanov's theorem ; Large deviation property for Markov chains ; Stationary distributions ; Entropy and relative entropy rates ; The rate function for Doubleton frequencies ; The rate function for Singleton frequencies --<br/> 6. Hidden Markov processes: basic properties : Equivalence of various hidden Markov models ; Three different-looking models ; Equivalence between the three models ; Computation of likelihoods ; Computation of likelihoods of output sequences ; The Viterbi algorithm ; The Baum-Welch algorithm --<br/> 7. Hidden Markov processes: the complete realization problem : Finite Hankel rank: a universal necessary condition ; Nonsufficiency of the finite Hankel rank condition ; An abstract necessary and sufficient condition ; Existence of regular quasi-realizations ; Spectral properties of alpha-mixing processes ; Ultra-mixing processes ; A sufficient condition for the existence of HMMs. 8. Some applications to computational biology : Some basic biology ; The genome ; The genetic code ; Optimal gapped sequence alignment ; Problem formulation ; Solution via dynamic programming ; Gene finding ; Genes and the gene-finding problem ; The GLIMMER family of algorithms ; The GENSCAN algorithm ; Protein classification ; Proteins and the protein classification problem ; Protein classification using profile hidden Markov models --<br/> 9. BLAST theory : BLAST theory: statements of main results ; Problem formulations ; THe moment generating function ; Statement of main results ; Application of main results ; BLAST theory: proofs of main results --<br/>Bibliography --<br/>Index.
520 ## - SUMMARY, ETC.
Summary, etc Explores important aspects of Markov and hidden Markov processes and the applications of these ideas to various problems in computational biology. This book provides a range of exercises, including drills to familiarize the reader with concepts and more advanced problems that require deep thinking about the theory.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computational biology.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Markov processes.
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Books
Holdings
Lost status Not for loan Home library Current library Date acquired Cost, normal purchase price Full call number Accession Number Koha item type
    ISI Library, Kolkata ISI Library, Kolkata 04/03/2016 3581.95 570.285 V655 136637 Books
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