Results 211 to 220 of about 852,410 (222)

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), 2005
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 (VI), followed by the middle temporal area (MT), in which nonlinear functions play important roles in the visual systems. In this paper,
Naohiro Ishii, Toshinori Deguchi, Hiroshi Sasaki   +2 more
openaire   +2 more sources

A neural network for motion computation [PDF]

IJCNN-91-Seattle International Joint Conference on Neural Networks, 1991
Summary form only given. The author discusses a neural network dedicated to the problem of motion computation, which requires a large amount of time on conventional computers. The initial estimation derived from both optical flow calculation and prediction-is the input of an anisotropic diffusion network, which regularizes the solution and preserves ...
openaire   +1 more source

Dynamics and neural network computation

International Journal of Quantum Chemistry, 1990
Computation is carried out by the motion of the state of a dynamical system. This description unites digital and “neural network” computation. The use of an energy function to understand and to program batch mode computation on feedback networks is reviewed.
openaire   +2 more sources

The Computational Capabilities of Neural Networks

2001
The (artificial) neural networks represent a widely applied computational paradigm that is an alternative to the conventional computers in many areas of artificial intelligence. By analogy with classical models of computation such as Turing machines which are useful for understanding the computational potential and limits of conventional computers, the
Jiří Šíma, Jiří Šíma
openaire   +2 more sources

Computation with Infinite Neural Networks

Neural Computation, 1998
For 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
openaire   +2 more sources

Granular Computing in Neural Networks

2001
The basic premise of granular computing is that, by reducing precision in our model of a system, we can suppress minor details and focus on the most significant relationships in the system. In this chapter, we will test this premise by defining a granular neural network and testing it on the Iris data set.
Scott Dick, Abraham Kandel
openaire   +2 more sources

Neural Networks and Computer Science

1989
My “position paper” can be summed up in the following sentence: There are strong scientific, technological and political reasons why massively parallel, (neural network) computation should be integrated into mainstream computer science. What follows is elaboration.
openaire   +2 more sources

Computation and Generalization in Neural Networks [PDF]

, 1993
Abstract : During this contract period, our research into backward propagation has led to a number of new theoretical and empirical results. We have developed a generalized version of backward propagation. In our generalized network, both gains and synapses are modified by a backward propagation procedure.
openaire   +1 more source

Neural Networks for Computational Neuroscience

2008
Computational neuroscience is an appealing interdisciplinary domain, at the interface between biology and computer science. It aims at understanding the experimental data obtained in neuroscience using several different kinds of models, one of which being artificial neural networks.
Meunier, David, Paugam-Moisy, Hélène
openaire   +2 more sources

Computational homogenization with Neural Networks

2015
International ...
Yvonnet, Julien, Le, B.A., He, Qi-Chang
openaire   +2 more sources