Showing 20 of 829 academic articles
M.J. Willis, Christine Di Massimo, Gary A. Montague, Ming T. Tham et al. • IEE Proceedings D Control Theory and Applications
(1991)
Artificial neural networks are made up of highly interconnected layers of simple ‘neuron-like’ nodes. The neurons act as nonlinear processing elements within the network. An attractive property of artificial neural networks is that, given t...
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DOI: https://doi.org/10.1049/ip-d.1991.0036
Gary A. Montague, Julian Morris • Trends in biotechnology
(1994)
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DOI: https://doi.org/10.1016/0167-7799(94)90048-5
M.T. Hagan, H.B. Demuth • Proceedings of the ... American Control Conference/Proceedings of the American Control Conference
(1999)
Provides a quick overview of neural networks and explains how they can be used in control systems. We introduce the multilayer perceptron neural network and describe how it can be used for function approximation. The backpropagation algorit...
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DOI: https://doi.org/10.1109/acc.1999.786109
J. Lee, Ronald C. Weger, S.K. Sengupta, Ronald M. Welch • IEEE Transactions on Geoscience and Remote Sensing
(1990)
It is shown that, using high-spatial-resolution data, very high cloud classification accuracies can be obtained with a neural network approach. A texture-based neural network classifier using only single-channel visible Landsat MSS imagery ...
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DOI: https://doi.org/10.1109/36.58972
• Choice Reviews Online
(1994)
At present, computers cannot think, make independent decisions, recognize visual and audible patterns, reach reliable conclusions without complete information or learn from their mistakes. The question this book and research into artificial...
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DOI: https://doi.org/10.5860/choice.32-2176
Lorenzo De Marinis, Marco Cococcioni, P. Castoldi, Nicola Andriolli • IEEE Access
(2019)
Photonic solutions are today a mature industrial reality concerning high speed, high throughput data communication and switching infrastructures. It is still a matter of investigation to what extent photonics will play a role in next-genera...
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DOI: https://doi.org/10.1109/access.2019.2957245
Soteris A. Kalogirou • Applied Energy
(2000)
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Open Access
DOI: https://doi.org/10.1016/s0306-2619(00)00005-2
S. Reynold Chu, Rahmat A. Shoureshi, Manoel Fernando Tenorio • IEEE Control Systems Magazine
(1990)
Two approaches are presented for utilization of neural networks in identification of dynamical systems. In the first approach, a Hopfield network is used to implement a least-squares estimation for time-varying and time-invariant systems. T...
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DOI: https://doi.org/10.1109/37.55121
Qiming Zhang, Haoyi Yu, Martina Barbiero, Baokai Wang et al. • Light Science & Applications
(2019)
The growing demands of brain science and artificial intelligence create an urgent need for the development of artificial neural networks (ANNs) that can mimic the structural, functional and biological features of human neural networks. Nano...
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DOI: https://doi.org/10.1038/s41377-019-0151-0
PMC: 6504946
Byoung S. Kim, Anthony J. Calise • Journal of Guidance Control and Dynamics
(1997)
The theoretical developmentofa direct adaptivetracking controlarchitectureusingneuralnetworks ispresented. Emphasis is placed on utilization of neural networks in a ight control architecture based on feedback linearization of the aircraft...
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DOI: https://doi.org/10.2514/2.4029
James Cannady (1998)
Misuse detection is the process of attempting to identify instances of network attacks by comparing current activity against the expected actions of an intruder. Most current approaches to misuse detection involve the use of rule-based expe...
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Leon Ong Chua, Lei Yang • IEEE International Symposium on Circuits and Systems proceedings
(2003)
A novel class of information-processing systems called cellular neural networks is proposed. Like neural networks, they are large-scale nonlinear circuits which process signals in real time. Like cellular automata, they are made of a massiv...
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DOI: https://doi.org/10.1109/iscas.1988.15089
Leon Ong Chua, L. Yang • IEEE Transactions on Circuits and Systems
(1988)
The theory of a novel class of information-processing systems, called cellular neural networks, which are capable of high-speed parallel signal processing, was presented in a previous paper (see ibid., vol.35, no.10, p.1257-72, 1988). A dyn...
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DOI: https://doi.org/10.1109/31.7601
Kevin Warwick • Institution of Engineering and Technology eBooks
(1995)
In this chapter, neural networks are discussed. The present field of neural networks links a number of closely related areas, such as parallel distributed processing, connectionism and neural computing, these being brought together with the...
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DOI: https://doi.org/10.1049/pbce053e_ch1
Anurag Shankar More, Makarand Chintamani Deo • Marine Structures
(2002)
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DOI: https://doi.org/10.1016/s0951-8339(02)00053-9
Leon Ong Chua, L. Yang • IEEE Transactions on Circuits and Systems
(1988)
A novel class of information-processing systems called cellular neural networks is proposed. Like neural networks, they are large-scale nonlinear analog circuits that process signals in real time. Like cellular automata, they consist of a m...
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DOI: https://doi.org/10.1109/31.7600
D.R. Baughman, Y. A. Liu • Elsevier eBooks
(1995)
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Open Access
DOI: https://doi.org/10.1016/c2009-0-21189-5
Hojjat Adeli • Computer-Aided Civil and Infrastructure Engineering
(2001)
The first journal article on neural network application in civil/structural engineering was published by in this journal in 1989. This article reviews neural network articles published in archival research journals since then. The emphasis ...
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DOI: https://doi.org/10.1111/0885-9507.00219
Mark S. Dougherty • Transportation Research Part C Emerging Technologies
(1995)
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DOI: https://doi.org/10.1016/0968-090x(95)00009-8
Abhay B. Bulsari • Elsevier eBooks
(1995)
Part 1 Theoretical issues: an introduction to artificial neural networks, D.T. Pham unsupervised neural learning, E. Oja back-propagation and its variations, D. Tsaptsinos the general approximation problem for feed-forward neural networks, ...
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