Journal Article10.1007/S11071-021-06580-3
A novel expectation–maximization-based separable algorithm for parameter identification of RBF-AR model
9
TL;DR: A novel regularized separable algorithm that takes advantage of the VP method and the expectation–maximization (EM) method to optimize the nonlinear parameters and automatically picks out the regularization parameters during the search process is considered.
read more
Abstract: The radial basis function network-based state-dependent autoregressive (RBF-AR) model has been widely used in modeling and prediction of nonlinear time series. The parameter identification of RBF-AR model can be reformulated as a separable nonlinear least squares problem. The variable projection (VP) algorithm has been proven to be valuable in solving such problems. However, for ill-posed problems, the classical VP algorithm usually yields unstable models. In this paper, we consider a novel regularized separable algorithm that takes advantage of the VP method and the expectation–maximization (EM) method. The proposed algorithm utilizes the VP algorithm to optimize the nonlinear parameters and automatically picks out the regularization parameters during the search process. Numerical results on real-world data and synthetic time series confirm the effectiveness of the proposed algorithm.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Regularization Of Inverse Problems
Lea Fleischer
- 01 Jan 2016
TL;DR: The regularization of inverse problems is universally compatible with any devices to read and is available in the book collection an online access to it is set as public so you can download it instantly.
1.5K
Parameter estimation for a controlled autoregressive autoregressive moving average system based on a recursive framework
TL;DR: In this article , an adaptive recursive estimation scheme based on a novel recursive framework is proposed for a controlled autoregressive auto-regressive moving average (CARARMA) system, which has two shortcomings in case of interference, namely, biased estimation and minima problems.
8
A variable projection-based parameter estimation algorithm for the nonsmooth separable nonlinear problems
12 May 2023
TL;DR: In this paper , a variable projection-based parameter estimation algorithm for the optimization of RBF-type models with nonsmooth constraint was proposed, where the parameters can be partitioned into a linear part and a nonlinear part.
A variable projection-based parameter estimation algorithm for the nonsmooth separable nonlinear problems
12 May 2023
TL;DR: In this article , a variable projection-based parameter estimation algorithm for the optimization of RBF-type models with nonsmooth constraint was proposed, where the parameters can be partitioned into a linear part and a nonlinear part.
Mechanical Dispatch Reliability Prediction for Civil Aircraft Considering Operational Parameters
TL;DR: In this article , the authors proposed an artificial neural network using radial basis function (RBF) as a kernel function, which has the best applicability in the prediction of multidimensional, small sample problems.
References
•Book
Classification and regression trees
Leo Breiman
- 01 Jan 1983
TL;DR: The methodology used to construct tree structured rules is the focus of a monograph as mentioned in this paper, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.
22.7K
Classification and regression trees
TL;DR: This article gives an introduction to the subject of classification and regression trees by reviewing some widely available algorithms and comparing their capabilities, strengths, and weakness in two examples.
Time series analysis, forecasting and control
P. Young,S. Shellswell +1 more
TL;DR: Time series analysis san francisco state university, 6 4 introduction to time series analysis, box and jenkins time seriesAnalysis forecasting and, th15 weeks citation classic eugene garfield, proc arima references 9 3 sas support, time series Analysis forecasting and control pambudi, timeseries analysis forecasting and Control george e.
14.1K
•Book
Regularization of Inverse Problems
Heinz W. Engl,Martin Hanke,Andreas Neubauer +2 more
- 31 Jul 1996
TL;DR: Inverse problems have been studied in this article, where Tikhonov regularization of nonlinear problems has been applied to weighted polynomial minimization problems, and the Conjugate Gradient Method has been used for numerical realization.
5.7K