IEEE transactions on neural networks最新文献

Editorial: The Blossoming of the IEEE Transactions on Neural Networks 社论:IEEE神经网络汇刊的繁荣期

IEEE transactions on neural networks Pub Date : 2011-12-01 DOI: 10.1109/TNN.2011.2176769

Derong Liu

引用次数: 61

Exponential synchronization of complex networks with finite distributed delays coupling. 有限分布延迟耦合复杂网络的指数同步。

IEEE transactions on neural networks Pub Date : 2011-12-01 Epub Date: 2011-10-10 DOI: 10.1109/TNN.2011.2167759

Cheng Hu, Juan Yu, Haijun Jiang, Zhidong Teng

引用次数: 71

Data mining based full ceramic bearing fault diagnostic system using AE sensors. 基于声发射传感器的全陶瓷轴承故障诊断系统。

IEEE transactions on neural networks Pub Date : 2011-12-01 Epub Date: 2011-10-10 DOI: 10.1109/TNN.2011.2169087

David He, Ruoyu Li, Junda Zhu, Mikhail Zade

{"title":"Data mining based full ceramic bearing fault diagnostic system using AE sensors.","authors":"David He, Ruoyu Li, Junda Zhu, Mikhail Zade","doi":"10.1109/TNN.2011.2169087","DOIUrl":"https://doi.org/10.1109/TNN.2011.2169087","url":null,"abstract":"Full ceramic bearings are considered the first step toward full ceramic, oil-free engines in the future. No research on full ceramic bearing fault diagnostics using acoustic emission (AE) sensors has been reported. Unlike their steel counterparts, signal processing methods to extract effective AE fault characteristic features and fault diagnostic systems for full ceramic bearings have not been developed. In this paper, a data mining based full ceramic bearing diagnostic system using AE based condition indicators (CIs) is presented. The system utilizes a new signal processing method based on Hilbert Huang transform to extract AE fault features for the computation of CIs. These CIs are used to build a data mining based fault classifier using a k-nearest neighbor algorithm. Seeded fault tests on full ceramic bearing outer race, inner race, balls, and cage are conducted on a bearing diagnostic test rig and AE burst data are collected. The effectiveness of the developed fault diagnostic system is validated using real full ceramic bearing seeded fault test data.","PeriodicalId":13434,"journal":{"name":"IEEE transactions on neural networks","volume":"22 12","pages":"2022-31"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TNN.2011.2169087","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30201405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 81

Data-based fault-tolerant control of high-speed trains with traction/braking notch nonlinearities and actuator failures. 基于数据的高速列车牵引/制动缺口非线性和执行器故障容错控制。

IEEE transactions on neural networks Pub Date : 2011-12-01 DOI: 10.1109/TNN.2011.2175451

Qi Song, Yong-Duan Song

{"title":"Data-based fault-tolerant control of high-speed trains with traction/braking notch nonlinearities and actuator failures.","authors":"Qi Song, Yong-Duan Song","doi":"10.1109/TNN.2011.2175451","DOIUrl":"https://doi.org/10.1109/TNN.2011.2175451","url":null,"abstract":"This paper investigates the position and velocity tracking control problem of high-speed trains with multiple vehicles connected through couplers. A dynamic model reflecting nonlinear and elastic impacts between adjacent vehicles as well as traction/braking nonlinearities and actuation faults is derived. Neuroadaptive fault-tolerant control algorithms are developed to account for various factors such as input nonlinearities, actuator failures, and uncertain impacts of in-train forces in the system simultaneously. The resultant control scheme is essentially independent of system model and is primarily data-driven because with the appropriate input-output data, the proposed control algorithms are capable of automatically generating the intermediate control parameters, neuro-weights, and the compensation signals, literally producing the traction/braking force based upon input and response data only--the whole process does not require precise information on system model or system parameter, nor human intervention. The effectiveness of the proposed approach is also confirmed through numerical simulations.","PeriodicalId":13434,"journal":{"name":"IEEE transactions on neural networks","volume":"22 12","pages":"2250-61"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TNN.2011.2175451","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30323484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 118

Guest editorial: special section on white box nonlinear prediction models. 客座评论:关于白盒非线性预测模型的特别部分。

IEEE transactions on neural networks Pub Date : 2011-12-01 DOI: 10.1109/TNN.2011.2177735

Bart Baesens, David Martens, Rudy Setiono, Jacek M Zurada

引用次数: 6

Passivity and stability analysis of reaction-diffusion neural networks with Dirichlet boundary conditions. Dirichlet边界条件下反应-扩散神经网络的无源性和稳定性分析。

IEEE transactions on neural networks Pub Date : 2011-12-01 Epub Date: 2011-10-14 DOI: 10.1109/TNN.2011.2170096

Jin-Liang Wang, Huai-Ning Wu, Lei Guo

引用次数: 92

Data-driven control for relative degree systems via iterative learning. 基于迭代学习的相对学位系统数据驱动控制。

IEEE transactions on neural networks Pub Date : 2011-12-01 Epub Date: 2011-11-18 DOI: 10.1109/TNN.2011.2174378

Deyuan Meng, Yingmin Jia, Junping Du, Fashan Yu

引用次数: 52

Symmetric nonnegative matrix factorization: algorithms and applications to probabilistic clustering. 对称非负矩阵分解:算法及其在概率聚类中的应用。

IEEE transactions on neural networks Pub Date : 2011-12-01 Epub Date: 2011-10-26 DOI: 10.1109/TNN.2011.2172457

Zhaoshui He, Shengli Xie, Rafal Zdunek, Guoxu Zhou, Andrzej Cichocki

引用次数: 175

Incremental learning from stream data. 从流数据中增量学习。

IEEE transactions on neural networks Pub Date : 2011-12-01 Epub Date: 2011-10-31 DOI: 10.1109/TNN.2011.2171713

Haibo He, Sheng Chen, Kang Li, Xin Xu

引用次数: 169

Bayesian multitask classification with Gaussian process priors. 高斯先验贝叶斯多任务分类。

IEEE transactions on neural networks Pub Date : 2011-12-01 Epub Date: 2011-10-10 DOI: 10.1109/TNN.2011.2168568

Grigorios Skolidis, Guido Sanguinetti

引用次数: 60