✦ LIBER ✦

Almost sure parameter estimation and convergence rates for hidden Markov models

✍ Scribed by R.J. Elliott; J.B. Moore

Publisher: Elsevier Science
Year: 1997
Tongue: English
Weight: 220 KB
Volume: 32
Category: Article
ISSN: 0167-6911
DOI: 10.1016/s0167-6911(97)00076-5

No coin nor oath required. For personal study only.

✦ Synopsis

A continuous-time v,~rsion of Kronecker's Lemma is established and used to give rates of convergence for parameter estimates in hidden Ma::kov models. (~) 1997 Elsevier Science B.V.

📜 SIMILAR VOLUMES

The semi-relaxed algorithm for estimatin

The semi-relaxed algorithm for estimating parameters of hidden Markov models

✍ Li Deng 📂 Article 📅 1991 🏛 Elsevier Science 🌐 English ⚖ 489 KB

For hidden Markov model (HMM) based speech recognition where the basic speech unit is smaller than the recognizer's output unit, the standard full Baum-Welch re-estimation procedure for the HMM training is very costly in computation. This is hecause it requires evaluation of the HMM output densities

Parameter estimation and restoration of

Parameter estimation and restoration of noisy images using Gibbs distributions in hidden Markov models

✍ Yunxin Zhao; Xinhua Zhuang; Les Atlas; Lars Anderson 📂 Article 📅 1992 🏛 Elsevier Science ⚖ 969 KB

Parameter estimation for nonlinear model

Parameter estimation for nonlinear models—convergence, data and parameter uncertainty, and constraints on parameter changes

✍ W.B. Walton 📂 Article 📅 1989 🏛 Elsevier Science 🌐 English ⚖ 841 KB

On-line almost-sure parameter estimation

On-line almost-sure parameter estimation for partially observed discrete-time linear systems with known noise characteristics

✍ Robert J. Elliott; Jason J. Ford; John B. Moore 📂 Article 📅 2002 🏛 John Wiley and Sons 🌐 English ⚖ 189 KB 👁 2 views