Journal ArticleDOI
System identification via state characterization
TLDR
Arbib and Zeiger's generalization of Ho's algorithm for system identification is presented from an alternative viewpoint called ''state characterization'' and it is proposed that state characterization may have practical application in determining an approximate, low order description of a complex system about which the authors have little prior information.About:
This article is published in Automatica.The article was published on 1972-09-01. It has received 69 citations till now. The article focuses on the topics: State space & Finite-state machine.read more
Citations
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Journal ArticleDOI
Learning regular sets from queries and counterexamples
TL;DR: In this article, the problem of identifying an unknown regular set from examples of its members and nonmembers is addressed, where the regular set is presented by a minimaMy adequate teacher, which can answer membership queries about the set and can also test a conjecture and indicate whether it is equal to the unknown set and provide a counterexample if not.
Journal ArticleDOI
Inductive Inference: Theory and Methods
Dana Angluin,Carl Smith +1 more
TL;DR: This survey highlights and explains the main ideas that have been developed in the study of inductive inference, with special emphasis on the relations between the general theory and the specific algorithms and implementations.
Journal ArticleDOI
Complexity of automaton identification from given data
TL;DR: The question of whether there is an automaton with n states which agrees with a finite set D of data is shown to be NP-complete, although identification-in-the-limit of finite automata is possible in polynomial time as a function of the size of D.
Journal ArticleDOI
Inference of Finite Automata Using Homing Sequences
TL;DR: These algorithms are the first which are provably effective for these problems, in the absence of a "reset," and also present probabilistic algorithms for permutation automata which do not require a teacher to supply counterexamples.
Book ChapterDOI
Inductive Inference, DFAs, and Computational Complexity
TL;DR: The results discussed determine the extent to which DFAs can be feasibly inferred, and highlight a number of interesting approaches in computational learning theory.
References
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Book
An Introduction to Multivariate Statistical Analysis
TL;DR: In this article, the distribution of the Mean Vector and the Covariance Matrix and the Generalized T2-Statistic is analyzed. But the distribution is not shown to be independent of sets of Variates.
Journal ArticleDOI
Introduction to Multivariate Statistical Analysis.
William G. Madow,T. W. Anderson +1 more
Journal ArticleDOI
Language identification in the limit
TL;DR: It was found that theclass of context-sensitive languages is learnable from an informant, but that not even the class of regular languages is learningable from a text.
Journal ArticleDOI
Finite automata and their decision problems
Michael O. Rabin,Dana Scott +1 more
TL;DR: Finite automata are considered as instruments for classifying finite tapes as well as generalizations of the notion of an automaton are introduced and their relation to the classical automata is determined.
Journal ArticleDOI
Mathematical description of linear dynamical systems
TL;DR: In this paper, it is shown that the input/output relations determine only one part of a system, that which is completely observable and completely controllable, and methods are given for calculating irreducible realization of a given impulse-response matrix.