Journal ArticleDOI
Brief paper: On the uniqueness of maximum likelihood identification
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TLDR
In this article, the local minimum points of a loss function for a common structure of a general form are investigated and sufficient conditions are given for the existence of a unique stationary point, which then also gives the desired global minimum.About:
This article is published in Automatica.The article was published on 1975-03-01. It has received 100 citations till now. The article focuses on the topics: Stationary point & Function (mathematics).read more
Citations
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Journal ArticleDOI
Adaptive IIR filtering
TL;DR: In this article, an overview of several methods, filter structures, and recursive algorithms used in adaptive infinite-impulse response (IIR) filtering is presented, and several important issues associated with adaptive IIR filtering, including stability monitoring, the SPR condition, and convergence are addressed.
Journal ArticleDOI
IIR system identification using cat swarm optimization
TL;DR: The IIR system identification task is formulated as an optimization problem and a recently introduced cat swarm optimization (CSO) is used to develop a new population based learning rule for the model.
Journal ArticleDOI
The Steiglitz-McBride identification algorithm revisited--Convergence analysis and accuracy aspects
Petre Stoica,Torsten Söderström +1 more
TL;DR: In this paper, the convergence and accuracy properties of the Steiglitz and McBride identification method are examined for a sufficiently large number of data points and it is shown that the method can converge to the true parameters only when the additive output noise is white.
Journal ArticleDOI
A new adaptive IIR filter
Hong Fan,W.K. Jenkins +1 more
TL;DR: In this paper, a family of stochastic approximation variants of the Steiglitz-McBride identification scheme was developed for adaptive IIR filtering, and the convergence was shown by computer simulation.
Journal ArticleDOI
Convergence properties of the generalised least squares identitication method
TL;DR: In this paper, the convergence properties of the generalized least squares method are analyzed and the number of local maximum points of the likelihood function is examined, and it is shown that this number is influenced by the signal to noise ratio.
References
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Journal ArticleDOI
System identification-A survey
Karl Johan Åström,Pieter Eykhoff +1 more
TL;DR: The survey explains the least squares method and several of its variants which may solve the problem of correlated residuals, viz. repeated and generalized least squares, maximum likelihood method, instrumental variable method, tally principle.
Journal ArticleDOI
On structural identifiability
TL;DR: In this article, structural identifiability is introduced to answer questions such as: To what extent is it possible to get insight into the internal structure of a system from input-output measurements? What experiments are necessary in order to determine the internal couplings uniquely?
Book ChapterDOI
Numerical Identification of Linear Dynamic Systems from Normal Operating Records
Karl Johan Åström,Torsten Bohlin +1 more
TL;DR: In this paper, a technique for numerical identification of a discrete time system from input/output samples is described, and strategies for control of the system are obtained using linear stochastic control theory.
Journal ArticleDOI
Maximum likelihood identification of stochastic linear systems
TL;DR: In this paper, the maximum likelihood estimation of the coefficients of multiple output linear dynamical systems and the noise correlations from the noisy measurements of input and output are discussed and conditions under which the estimates converge to their true values as the number of measurements tend to infinity.
Journal ArticleDOI
Uniqueness of the maximum likelihood estimates of the parameters of an ARMA model
TL;DR: In this paper, conditions for the existence of a unique global and local minimum are given for a mixed autoregressive moving average (MAMA) model with respect to both local and global extrema.