Suchergebnisse - "stochastic gradient algorithm"

Distributed Extended Stochastic Gradient Algorithm for Joint Identification of System Parameters and Noise Model Parameters: Distributed extended stochastic gradient algorithm for joint identification of system parameters and noise model parameters

Autoren: Die Gan Ren Yan Shuning Chen et al.

Quelle: SIAM Journal on Control and Optimization. 63:650-675

Schlagwörter: distributed identification, ARMAX model, colored noise, Randomized algorithms, Networked control, stochastic gradient algorithm, Stochastic systems in control theory (general), almost sure convergence, System identification, sensor network

Dateibeschreibung: application/xml

Highly Efficient Two-Stage Filtering-Based Maximum Likelihood Stochastic Gradient Algorithm for Multiple-Input Multiple-Output Systems

Autoren: Huihui Wang Ximei Liu

Quelle: Circuits, Systems, and Signal Processing. 44:5608-5639

Convergence analysis of a proximal stochastic gradient algorithm with adaptive sampling for non-convex and non-smooth composite optimization problems

Quelle: Journal of Nonlinear and Variational Analysis. 9

Line Search Stochastic Gradient Algorithm with A-priori Rule for Monitoring the Control of the Variance

Autoren: Giorgia Franchini Federica Porta Valeria Ruggiero et al.

Quelle: Lecture Notes in Computer Science ISBN: 9783031812408

Schlagwörter: adaptive hyper-parameter setting, deep learning, line search strategy, machine learning, stochastic gradient methods, variance condition, adaptive hyper-parameter setting, deep learning, line search strategy, machine learning, stochastic gradient methods, variance condition

Zugangs-URL: https://hdl.handle.net/11392/2580170
https://doi.org/10.1007/978-3-031-81241-5_7

A Bias-Correction Decentralized Stochastic Gradient Algorithm with Momentum Acceleration

Autoren: Hu, Yuchen Chen, Xi Liu, Weidong et al.

Index Begriffe: Computer Science - Machine Learning, Computer Science - Distributed, Parallel, and Cluster Computing, Mathematics - Optimization and Control, Statistics - Machine Learning, text

URL: http://arxiv.org/abs/2501.19082

Identification of a nonlinear rational model based on bias compensated multi-innovation stochastic gradient algorithm

Autoren: S. X. Jing R. R. Liu L. Chen

Quelle: Automatika, Vol 63, Iss 4, Pp 785-792 (2022)
Automatika : časopis za automatiku, mjerenje, elektroniku, računarstvo i komunikacije
Volume 63
Issue 4

Schlagwörter: T59.5, Automation, 0209 industrial biotechnology, Control engineering systems. Automatic machinery (General), adaptive modelling, TJ212-225, Nonlinear rational model, 0202 electrical engineering, electronic engineering, information engineering, bias compensation, stochastic gradient algorithm, 02 engineering and technology, parameter estimation

Dateibeschreibung: application/pdf

Zugangs-URL: https://doaj.org/article/9c579847d3df43b79066e24d39572826

Fractional Stochastic Gradient Algorithm for Time-Delayed Models With Piece-Wise Linear Input Using Self-Organizing Maps Method

Autoren: Jia Tang

Quelle: IEEE Access, Vol 10, Pp 131053-131060 (2022)

Schlagwörter: 0209 industrial biotechnology, nonlinear model, fractional stochastic gradient algorithm, self-organizing maps, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, System identification, multi-innovation, piece-wise linear, TK1-9971

Zugangs-URL: https://doaj.org/article/50b00c500aa5491d9494c9e37117968d

Online Distributed Stochastic Gradient Algorithm for Nonconvex Optimization With Compressed Communication

Autoren: Jueyou Li Chaojie Li Jing Fan et al.

Quelle: IEEE Transactions on Automatic Control. 69:936-951

1/t-Polyak Stepsize for the Stochastically Controlled Stochastic Gradient Algorithm

Quelle: Advances in Applied Mathematics. 13:1008-1017

Improved Redundant Rule-Based Stochastic Gradient Algorithm for Time-Delayed Models Using Lasso Regression

Autoren: Hangtao Zhao Lixin Lv Yuejiang Ji

Quelle: IEEE Access, Vol 10, Pp 3336-3342 (2022)

Schlagwörter: lasso regression, Parameter estimation, 0202 electrical engineering, electronic engineering, information engineering, stochastic gradient algorithm, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, redundant rule, time-delayed model, TK1-9971

Zugangs-URL: https://ieeexplore.ieee.org/ielx7/6287639/6514899/09663158.pdf
https://doaj.org/article/1bf92502cb384635a54ab371169cdfa2

Parameter identification of vertical plane model for autonomous underwater vehicle based on hierarchical multi-innovation stochastic gradient algorithm

Autoren: Yang Liu Longjin Wang Shun An et al.

Quelle: Measurement. 252:117316

Identification Method Based on Improved Hierarchical Multi-innovation Stochastic Gradient Algorithm

Autoren: Pan Hui Li Zhengyang

Quelle: 2023 8th International Conference on Power and Renewable Energy (ICPRE). :148-155

An Adaptive Stochastic Gradient Algorithm Based on FISTA for Convex Optimization.

Autoren: Zhai, Yujia Xue, Dan Qi, Rulei et al.

Quelle: Computational Mathematics & Mathematical Physics. Oct2025, Vol. 65 Issue 10, p2342-2361. 20p.

Schlagwörter: *CONVEX programming, *OPTIMIZATION algorithms, *CONSTRAINED optimization, *PROCESS optimization, *EMPIRICAL research

Model transformation based distributed stochastic gradient algorithm for multivariate output-error systems

Autoren: Qinyao Liu Feiyan Chen

Quelle: International Journal of Systems Science. 54:1484-1502

Schlagwörter: 0209 industrial biotechnology, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Decomposition‐based over‐parameterization forgetting factor stochastic gradient algorithm for Hammerstein‐Wiener nonlinear systems with non‐uniform sampling: Decomposition-based over-parameterization forgetting factor stochastic gradient algorithm for Hammerstein-Wiener nonlinear systems with non-uniform sampling

Autoren: Tasawar Hayat Yongsong Xiao Feng Ding et al.

Quelle: International Journal of Robust and Nonlinear Control. 31:6007-6024

Schlagwörter: Hammerstein-Wiener model, 0209 industrial biotechnology, Estimation and detection in stochastic control theory, over-parameterization, decomposition technique, Nonlinear systems in control theory, 02 engineering and technology, nonlinear system, parameter estimation

Dateibeschreibung: application/xml

Zugangs-URL: https://onlinelibrary.wiley.com/doi/10.1002/rnc.5576

Finite Sample and Large Deviations Analysis of Stochastic Gradient Algorithm with Correlated Noise

Autoren: Yin, George Krishnamurthy, Vikram

Index Begriffe: Computer Science - Machine Learning, Electrical Engineering and Systems Science - Systems and Control, text

URL: http://arxiv.org/abs/2410.08449

ADAPTIVE STOCHASTIC GRADIENT ALGORITHM FOR BLACK BOX MULTI OBJECTIVE LEARNING

Autoren: Ye, F Lyu, Y Wang, X et al.

Index Begriffe: Conference Proceeding

URL: http://hdl.handle.net/10453/185398
12th International Conference on Learning Representations, ICLR 2024

Bias compensated stochastic gradient algorithm for identification of an ARX‐type nonlinear rational model and its application in modeling of the dynamic of the cellular toxicity

Autoren: Shaoxue Jing Janice Kiely Richard Luxton

Quelle: International Journal of Robust and Nonlinear Control. 32:5268-5280

Schlagwörter: 0209 industrial biotechnology, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Multierror stochastic gradient algorithm for identification of a Hammerstein system with random noise and its application in the modeling of a continuous stirring tank reactor

Autoren: Shaoxue Jing

Quelle: Optimal Control Applications and Methods. 44:1510-1522

Schlagwörter: 0209 industrial biotechnology, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Zugangs-URL: https://onlinelibrary.wiley.com/doi/10.1002/oca.2760

Efficient and fast estimation of the geometric median in Hilbert spaces with an averaged stochastic gradient algorithm

Autoren: CARDOT, HERVÉ CÉNAC, PEGGY ZITT, PIERRE-ANDRÉ

Quelle: Bernoulli, 2013 Feb 01. 19(1), 18-43.

Zugangs-URL: http://dx.doi.org/10.3150/11-BEJ390