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Titlebook: Adaptive Control with Recurrent High-order Neural Networks; Theory and Industria George A. Rovithakis,Manolis A. Christodoulou Book 2000 Sp

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發(fā)表于 2025-3-21 19:55:48 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Adaptive Control with Recurrent High-order Neural Networks
期刊簡稱Theory and Industria
影響因子2023George A. Rovithakis,Manolis A. Christodoulou
視頻videohttp://file.papertrans.cn/145/144618/144618.mp4
發(fā)行地址The applications of neural networks are areas of considerable interest at present.Concise and very tightly targetted text.Will be of interest to academic control engineers outside the series‘ normal i
學(xué)科分類Advances in Industrial Control
圖書封面Titlebook: Adaptive Control with Recurrent High-order Neural Networks; Theory and Industria George A. Rovithakis,Manolis A. Christodoulou Book 2000 Sp
影響因子The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies ... , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. Neural networks is one of those areas where an initial burst of enthusiasm and optimism leads to an explosion of papers in the journals and many presentations at conferences but it is only in the last decade that significant theoretical work on stability, convergence and robustness for the use of neural networks in control systems has been tackled. George Rovithakis and Manolis Christodoulou have been interested in these theoretical problems and in the practical aspects of neural network applications to industrial problem
Pindex Book 2000
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T4 Bacteriophage as a Model Genetic System,ven pairs of input-output data (which may be related by an unknown algebraic relation, a so-called “static” function) the network is trained to learn the particular input-output map. Theoretical work by several researchers, including Cybenko [16], and Funahashi [24], have proven that, even with one
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T4 Bacteriophage as a Model Genetic System,ctivity, competitiveness and viability. Production scheduling (i.e., organization and control of production operations in manufacturing systems), is essential for the efficient operation of a production environment. Production scheduling actually concerns the efficient allocation over time of resour
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Conjugation and the , Paradigm,This chapter is devoted to the development of indirect adaptive control techniques (based on RHONNs), for controlling nonlinear dynamical systems, with highly uncertain and possibly unknown nonlinearities.
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Advances in Industrial Controlhttp://image.papertrans.cn/a/image/144618.jpg
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