Maximum likelihood least squares identification method for active noise control systems with autoregressive moving average noise

DOI10.1016/j.automatica.2016.02.011zbMath1338.93385OpenAlexW2300160183MaRDI QIDQ286225

Muhammad Saeed Aslam

Publication date: 20 May 2016

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2016.02.011

zbMATH Keywords

parameter estimationmaximum likelihoodleast squaresactive noise controlfiltered-X least mean square (FXLMS) algorithmonline secondary path modeling

Mathematics Subject Classification ID

Least squares and related methods for stochastic control systems (93E24) Identification in stochastic control theory (93E12)

Related Items (6)

Data filtering based maximum likelihood extended gradient method for multivariable systems with autoregressive moving average noise ⋮ Self-adapting variable step size strategies for active noise control systems with acoustic feedback ⋮ Parameter estimation algorithms for Hammerstein output error systems using Levenberg-Marquardt optimization method with varying interval measurements ⋮ The maximum likelihood least squares based iterative estimation algorithm for bilinear systems with autoregressive moving average noise ⋮ Composite learning control of robotic systems: a least squares modulated approach ⋮ The data filtering based generalized stochastic gradient parameter estimation algorithms for multivariate output-error autoregressive systems using the auxiliary model

Cites Work

• Maximum likelihood least squares identification for systems with autoregressive moving average noise
• Performance analysis of multi-innovation gradient type identification methods
• Accuracy analysis of time domain maximum likelihood method and sample maximum likelihood method for errors-in-variables and output error identification
• On the equivalence of time and frequency domain maximum likelihood estimation
• Maximum likelihood estimation for directional conditionally autoregressive models
• Designing a new robust on-line secondary path modeling technique for feedforward active noise control systems
• Maximum likelihood least squares identification method for input nonlinear finite impulse response moving average systems
• Testing the capital asset pricing model with local maximum likelihood methods

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