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Original Essays | September 15, 2014

Lois Leveen: IMG Forsooth Me Not: Shakespeare, Juliet, Her Nurse, and a Novel



There's this writer, William Shakespeare. Perhaps you've heard of him. He wrote this play, Romeo and Juliet. Maybe you've heard of it as well. It's... Continue »
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    Juliet's Nurse

    Lois Leveen 9781476757445

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Stochastic Modelling and Applied Probability #29: Hidden Markov Models

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Stochastic Modelling and Applied Probability #29: Hidden Markov Models Cover

 

Synopses & Reviews

Publisher Comments:

As more applications are found, interest in Hidden Markov Models continues to grow. Following comments and feedback from colleagues, students and other working with Hidden Markov Models the corrected 3rd printing of this volume contains clarifications, improvements and some new material, including results on smoothing for linear Gaussian dynamics. In Chapter 2 the derivation of the basic filters related to the Markov chain are each presented explicitly, rather than as special cases of one general filter. Furthermore, equations for smoothed estimates are given. The dynamics for the Kalman filter are derived as special cases of the authors' general results and new expressions for a Kalman smoother are given. The Chapters on the control of Hidden Markov Chains are expanded and clarified. The revised Chapter 4 includes state estimation for discrete time Markov processes and Chapter 12 has a new section on robust control.

Table of Contents

Preface.- Part I Introduction: 1.Hidden Markov Model Processing.- Part II Discrete-Time HMM Estimation: 2.Discrete States and Discrete Observations.- 3.Continuous-Range Observations.- 4.Continuous-Range States and Observations.- 5.A General Recursive Filter.- 6.Practical Recursive Filters.- Part III Continuous-Time HMM Estimation: 7.Discrete-Range States and Observations.- 8.Markov Chains in Brownian Motion .- Part IV Two-Dimensional HMM Estimation: 9.Hidden Markov Random Fields.- Part V HMM Optimal Control: 10.Discrete-Time HMM Control.- 11.Risk-Sensitive Control of HMM.- 12.Continuous-Time HMM Control.- Appendices: A.Basic Probability Concepts.- B.Continuous-Time Martingale Representation. -References.- Index.

Product Details

ISBN:
9781441928412
Author:
Elliott, Robert J.
Publisher:
Springer
Author:
Aggoun, Lakhdar
Author:
Moore, John B.
Location:
New York, NY
Subject:
Applied
Subject:
93E11, 93E20, 60G35, 60H30
Subject:
EM algorithm
Subject:
Hidden Markov chains
Subject:
Filtering
Subject:
Parameter estimation.
Subject:
Stochastic Control
Subject:
Systems Theory, Control
Subject:
Probability Theory and Stochastic Processes
Subject:
Quantitative Finance
Subject:
Mathematics-Applied
Subject:
System Theory
Subject:
Mathematics
Subject:
Language, literature and biography
Subject:
mathematics and statistics
Subject:
Systems theory.
Subject:
Distribution (Probability theory)
Subject:
Finance
Copyright:
Edition Description:
Softcover reprint of hardcover 1st ed. 1995
Series:
Stochastic Modelling and Applied Probability
Series Volume:
29
Publication Date:
20101201
Binding:
TRADE PAPER
Language:
English
Pages:
376
Dimensions:
235 x 155 mm 595 gr

Related Subjects

Business » Accounting and Finance
Science and Mathematics » Mathematics » Applied
Science and Mathematics » Mathematics » Probability and Statistics » General
Science and Mathematics » Mathematics » Probability and Statistics » Statistics
Science and Mathematics » Physics » General

Stochastic Modelling and Applied Probability #29: Hidden Markov Models New Trade Paper
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