Q
Qinghua Zhang
Researcher at French Institute for Research in Computer Science and Automation
Publications - 130
Citations - 8565
Qinghua Zhang is an academic researcher from French Institute for Research in Computer Science and Automation. The author has contributed to research in topics: Fault detection and isolation & Nonlinear system. The author has an hindex of 31, co-authored 124 publications receiving 8124 citations.
Papers
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Journal ArticleDOI
Wavelet networks
Qinghua Zhang,Albert Benveniste +1 more
TL;DR: A wavelet network concept, which is based on wavelet transform theory, is proposed as an alternative to feedforward neural networks for approximating arbitrary nonlinear functions.
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Nonlinear black-box modeling in system identification: a unified overview
Jonas Sjöberg,Qinghua Zhang,Lennart Ljung,Albert Benveniste,Bernard Delyon,Pierre-Yves Glorennec,Håkan Hjalmarsson,Anatoli Juditsky +7 more
TL;DR: What are the common features in the different approaches, the choices that have to be made and what considerations are relevant for a successful system-identification application of these techniques are described, from a user's perspective.
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Using wavelet network in nonparametric estimation
TL;DR: Algorithms for wavelet network construction are proposed for the purpose of nonparametric regression estimation and particular attentions are paid to sparse training data so that problems of large dimension can be better handled.
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Adaptive observer for multiple-input-multiple-output (MIMO) linear time-varying systems
TL;DR: For joint state-parameter estimation in linear time-varying (LTV) multiple-input-multiple-output (MIMO) systems, an approach to the design of adaptive observers is proposed that is conceptually simple and computationally efficient and global exponential convergence is established for noise-free systems.
Journal ArticleDOI
Nonlinear black-box models in system identification: mathematical foundations
Anatoli Juditsky,Håkan Hjalmarsson,Albert Benveniste,Bernard Delyon,Lennart Ljung,Jonas Sjöberg,Qinghua Zhang +6 more
TL;DR: Different approximation methods are considered, and the acquired approximation experience is applied to estimation problems, and wavelet and ‘neuron’ approximations are introduced, and shown to be spatially adaptive.