Learning Finite Automaton from Noisy Observations -- A Simple Instance of a Bidirectional Signal-to-symbol

Result code in IS VaVaI

RIV/68407700:21230/04:00105693 - isvavai.cz

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Learning Finite Automaton from Noisy Observations -- A Simple Instance of a Bidirectional Signal-to-symbol

Original language description

This report investigates the way how to learn the finite automaton model of the activity observed in real world. The related theory is reviewed, solution proposed and experiments conducted. Learning finite automaton is similar to learning a discrete Hidden Markov Model (HMM) using a variant of EM algorithm. We used J. Dupa{v c}'s discrete HMM Toolbox in Matlab. The experimental part of this work deals with learning HMM from a synthetic training set generated from a known model. This approach provides us with ground truth.

Czech name

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Czech description

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Type

O - Miscellaneous

CEP classification

JD - Use of computers, robotics and its application

OECD FORD branch

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Project

GA102/03/0440: Recognizing human activities for automated video surveillance

Continuities

R - Projekt Ramcoveho programu EK

Publication year

2004

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů