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Proceedings of ICNN'95 - International Conference on Neural Networks, 2002
In this paper, we discuss an approach for designing the computational neural network, which is mainly composed of a hardlimiter neuron, a updated neuron, and a search function neuron, to solve some computational problems. The computation-by-search scheme can effectively solve some complicated problems in the condition that their search functions can be
Jar-Ferr Yang, Chi-Ming Chen
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In this paper, we discuss an approach for designing the computational neural network, which is mainly composed of a hardlimiter neuron, a updated neuron, and a search function neuron, to solve some computational problems. The computation-by-search scheme can effectively solve some complicated problems in the condition that their search functions can be
Jar-Ferr Yang, Chi-Ming Chen
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Neural computations by networks of oscillators
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium, 2000We describe here how a network of oscillators can perform neural computations. In particular, it shown how the connectivity within the network can be created to memorize data in terms of phase relations between synchronized states. The memorized states are extracted through correlation calculations. The influence of noise on the system is discussed.
Frank C. Hoppensteadt +1 more
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Layered Neural Networks Computations
Sixth International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing and First ACIS International Workshop on Self-Assembling Wireless Networks (SNPD/SAWN'05), 2005Among prominent features of the visual networks, movement detections are carried out in the visual cortex. The visual cortex for the movement detection, consist of two layered networks, called the primary visual cortex (VI), followed by the middle temporal area (MT), in which nonlinear functions play important roles in the visual systems. In this paper,
Naohiro Ishii +2 more
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Computing with structured neural networks
Computer, 1988The authors are concerned with how one can design, realize, and analyze networks that embody the specific computational structures needed to solve hard problems. They focus on the design and use of massively parallel connectionist computational models, particularly in artificial intelligence.
Jerome A. Feldman +2 more
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Future Generation Computer Systems, 1991
Abstract In this paper, we give a general presentation of neural networks, showing their links and differences with Artificial Intelligence and neurosciences. We provide the general formalism of neural networks and describe two neural networks learning algorithms: gradient backpropagation and learning vector quantization.
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Abstract In this paper, we give a general presentation of neural networks, showing their links and differences with Artificial Intelligence and neurosciences. We provide the general formalism of neural networks and describe two neural networks learning algorithms: gradient backpropagation and learning vector quantization.
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Computation with Infinite Neural Networks
Neural Computation, 1998For neural networks with a wide class of weight priors, it can be shown that in the limit of an infinite number of hidden units, the prior over functions tends to a gaussian process. In this article, analytic forms are derived for the covariance function of the gaussian processes corresponding to networks with sigmoidal and gaussian hidden units. This
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Neural Networks and Computer Vision
Hand ClinicsSince the conception of the artificial neuron in 1943, neural networks have developed into multi-layer models enabling image recognition, speech recognition, personalized recommendation for web browsing, social media content, and virtual assistants. Harnessing this power, researchers have developed models that can potentially improve both access to ...
Alfred P, Yoon, Kevin C, Chung
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Vector Operations in Neural Networks Computations
2013 14th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, 2013Nonlinearity is an important factor in the biological visual neural networks. Among prominent features of the visual networks, movement detections are carried out in the visual cortex. The visual cortex for the movement detection, consist of two layered networks, called the primary visual cortex (V1), followed by the middle temporal area (MT), in which
Naohiro Ishii +3 more
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Brain, Neural Networks, and Computation
Reviews of Modern Physics, 1999The method by which brain produces mind has for centuries been discussed in terms of the most complex engineering and science metaphors of the day. Descartes described mind in terms of interacting vortices. Psychologists have metaphorized memory in terms of paths or traces worn in a landscape, a geological record of our experiences.
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