Search Results - "Stochastic gradient algorithm"

Parameter estimation of fractional‐order Hammerstein state space system based on the extended Kalman filter by Bi, Yiqun, Ji, Yan

“…Summary This paper addresses the combined estimation issues of the parameters and states for fractional‐order Hammerstein state space systems with colored…”
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Recursive coupled projection algorithms for multivariable output-error-like systems with coloured noises by Pan, Jian, Ma, Hao, Zhang, Xiao, Liu, Qinyao, Ding, Feng, Chang, Yufang, Sheng, Jie

“…By combining the coupling identification concept with the gradient search, this study develops a partially coupled generalised extended projection algorithm…”
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A stochastic multiple gradient descent algorithm by Mercier, Quentin, Poirion, Fabrice, Désidéri, Jean-Antoine

“…•A new gradient-based algorithm for stochastic multiobjective optimization problem.•Mean-square and almost-sure convergence of the algorithm proven.•Algorithm…”
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Online distribution system state estimation via stochastic gradient algorithm by Huang, Jianqiao, Zhou, Xinyang, Cui, Bai

“…Distribution network operation is becoming more challenging because of the growing integration of intermittent and volatile distributed energy resources…”
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The Value of Collaboration in Convex Machine Learning with Differential Privacy by Wu, Nan, Farokhi, Farhad, Smith, David, Kaafar, Mohamed Ali

“…In this paper, we apply machine learning to distributed private data owned by multiple data owners, entities with access to non-overlapping training datasets…”
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Weighted multi-innovation extended stochastic gradient identification for multivariable Hammerstein nonlinear systems based on multi-signal processing by Lyu, Bensheng, Wang, Qiang, Xu, Yanling, Zhang, Huajun, Cai, Chunbo

“…Multivariable Hammerstein nonlinear systems contain a sum of some bilinear parameter functions, which is hard to convert into a standard regressive form for…”
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Performance analysis of the generalised projection identification for time-varying systems by Ding, Feng, Xu, Ling, Zhu, Quanmin

“…The least mean square methods include two typical parameter estimation algorithms, which are the projection algorithm and the stochastic gradient algorithm,…”
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Identifying Cognitive Radars - Inverse Reinforcement Learning using Revealed Preferences by Krishnamurthy, Vikram, Angley, Daniel, Evans, Rob, Moran, Bill

“…We consider an inverse reinforcement learning problem involving us versus an enemy radar equipped with a Bayesian tracker. By observing the emissions of the…”
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Hierarchical multi-innovation generalised extended stochastic gradient methods for multivariable equation-error autoregressive moving average systems by Xu, Ling, Ding, Feng, Lu, Xian, Wan, Lijuan, Sheng, Jie

“…This study presents the modelling technology of multivariable equation-error autoregressive moving average (EEARMA) systems through observational data of…”
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Hierarchical gradient parameter estimation algorithms for fractional order Wiener OEARMA system by Li, Junhong, Zhang, Hongrui, Xiao, Kang, Gu, Juping

“…In this paper, the identification of fractional order Wiener output error auto-regressive moving average (OEARMA) systems is discussed. The dynamic part of the…”
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Parameter identification algorithm for ship manoeuvrability and wave peak model based multi-innovation stochastic gradient algorithm use data filtering technique by Liu, Yang, An, Shun, Wang, Longjin, He, Yan, Fan, Zhimin

“…This paper addresses the issue of identifying ship motion parameters and wave peak frequency. Utilising the Euler discretisation principle, we establish a…”
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Particle filtering-based recursive identification for controlled auto-regressive systems with quantised output by Ding, Jie, Chen, Jiazhong, Lin, Jinxing, Jiang, Guoping

“…Recursive prediction error method is one of the main tools for analysis of controlled auto-regressive systems with quantised output. In this study, a recursive…”
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New Scalable and Efficient Online Pairwise Learning Algorithm by Gu, Bin, Bao, Runxue, Zhang, Chenkang, Huang, Heng

“…Pairwise learning is an important machine-learning topic with many practical applications. An online algorithm is the first choice for processing streaming…”
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Research on a learning rate with energy index in deep learning by Zhao, Huizhen, Liu, Fuxian, Zhang, Han, Liang, Zhibing

“…The stochastic gradient descent algorithm (SGD) is the main optimization solution in deep learning. The performance of SGD depends critically on how learning…”
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Predicting Hepatitis B to be acute or chronic in an infected person using machine learning algorithm by Vijayalakshmi, C., Mohideen, S. Pakkir

“…•Hepatitis B is a viral infection which causes liver damage.•In this paper it is discussed about Hepatitis B found positive in a person's blood test is acute…”
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Parameter estimation algorithms for dynamical response signals based on the multi-innovation theory and the hierarchical principle by Xu, Ling, Ding, Feng

“…In this study, the authors consider the parameter estimation problem of the response signal from a highly non-linear dynamical system. The step response…”
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Adaptive Time Synchronization in Time Sensitive-Wireless Sensor Networks Based on Stochastic Gradient Algorithms Framework by Abdul-Rashid, Ramadan, Chan, Kar Tim, Rahman, Mohd Amiruddin Abd, Sangaiah, Arun Kumar

“…This study proposes a novel time-synchronization protocol inspired by stochastic gradient algorithms. The clock model of each network node in this synchronizer…”
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Online estimation of the asymptotic variance for averaged stochastic gradient algorithms by Godichon, Antoine

“…Stochastic gradient algorithms are more and more studied since they can deal efficiently and online with large samples in high dimensional spaces. In this…”
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Stochastic differential equation approximations of generative adversarial network training and its long-run behavior by Cao, Haoyang, Guo, Xin

“…This paper analyzes the training process of generative adversarial networks (GANs) via stochastic differential equations (SDEs). It first establishes SDE…”
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Multikernel Passive Stochastic Gradient Algorithms and Transfer Learning by Krishnamurthy, Vikram, Yin, George

“…This article develops a novel passive stochastic gradient algorithm. In passive stochastic approximation, the stochastic gradient algorithm does not have…”
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