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A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains

Leonard E. Baum, +3 more
- 01 Feb 1970 - 
- Vol. 41, Iss: 1, pp 164-171
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This article is published in Annals of Mathematical Statistics.The article was published on 1970-02-01 and is currently open access. It has received 4618 citations till now. The article focuses on the topics: Examples of Markov chains & Markov chain.

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Citations
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Journal ArticleDOI

Speechreading using Probabilistic Models

TL;DR: A speechreading (lip-reading) system, where the extracted features are modeled by Gaussian distributions and their temporal dependencies by hidden Markov models, which achieves an accuracy about equivalent to that of untrained humans.
Proceedings ArticleDOI

Recognition of Equations Using a Two-Dimensional Stochastic Context-Free Grammar

TL;DR: This work proposes using two-dimensional stochastic context-free grammars for image recognition, in a manner analogous to using hidden Markov models for speech recognition, and demonstrates the value of the approach in a system that recognizes printed, noisy equations.
Journal ArticleDOI

Reversible jump, birth‐and‐death and more general continuous time Markov chain Monte Carlo samplers

TL;DR: In this article, it was shown that the reversible jump chain converges to a limiting continuous-time birth-and-death process for mixtures of distributions and hidden Markov models.
Journal ArticleDOI

Bayesian Gaussian Mixture Linear Inversion for Geophysical Inverse Problems

TL;DR: A Bayesian linear inversion methodology based on Gaussian mixture models and its application to geophysical inverse problems is presented in this article, where a recursive exact solution to an approximation of the posterior distribution of the inverse problem is proposed.
References
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Journal ArticleDOI

An inequality with applications to statistical estimation for probabilistic functions of Markov processes and to a model for ecology

TL;DR: In this paper, a polynomial with nonnegative coefficients homogeneous of degree d in its variables is shown to be polynomially homogeneous unless 3(3(x))>P(x), where 3(x)=x.
Book

The gamma function

Emil Artin, +1 more
Book ChapterDOI

The Gamma Function

TL;DR: The Gamma function as discussed by the authors is a generalized factorial function that can be used to estimate the probability distribution of a probability distribution, and it has been used in many applications, e.g., as part of probability distributions.
Journal ArticleDOI

An Inequality

Joel Brenner