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Your search keyword '"Neural Networks"' showing total 5 results
Start Over Descriptor "Neural Networks" Publication Year Range More than 50 years ago
5 results on '"Neural Networks"'

1. PLEXUS--An On-line System for Modeling Neural Networks.

Author

Dill, J. C., Randall, D. L., and Richer, I.

Subjects
*ARTIFICIAL neural networks, *NEURAL circuitry, *COMPUTER simulation, *DATA analysis, *NEUROPHYSIOLOGY, *LIBRARIES
Abstract

A description is presented of PLEXUS, a system which enables a user to construct and specify a neural network, to analyze the output data produced by the network, and to store and retrieve networks and data from a library. The system, operated entirely from a digital display unit, interacts directly with the user and permits easy and rapid transitions between the various phases of the modeling process. PLEXUS is designed to complement neurophysiological research so that the systematic development of neural models can be coordinated with experimental work. PLEXUS networks are built up from components representing individual neurons, external stimuli, and interconnecting fibers, each component being of a relatively detailed nature. Pro- vision is also made for the use of experimental data as input to a network. Convenient means for specification and modification of a network and extensive error-checking capabilities are provided. Data resulting from the simulation of a network may be analyzed by a variety of techniques ranging from examinations of the gross characteristics of the data to the determination of detailed statistical properties. [ABSTRACT FROM AUTHOR]

Published
1968
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3. Study on Environmental Conservation in Suo Nada Region (1st Report) : Stream Line Analysis and Investigation on Atmospheric Diffusion near the Ground in a Small Scale Headland

Subjects
architecture, simplification, 土木工学, structure, neural networks, optimization, 環境学, genetic algorithms
Abstract

Characteristics of the wind structure near the ground and the atmospheric diffusion on small scale headland (Chigasaki, Saga Pref., 1000m. 800m) are investigated by means of flag net-work observation (for the former) and the fluorescent particle (F. P.) tracer technique (for the latter) for Jul. 10-16,1969. Results of stream line analysis and the comparison of the observed particle concentration by rotor rod samplers network with the calculated ones by the diffusion equation of the continuous point source and Pasquill's formula, are as follows : 1) When south-western wind is stronger than 5m/s, the vertical wind fields are often appeared at the southern part of the headland. 2) In other west and north-estern wind field, vortex are not appeared so much as in the south-western wind. 3) In this investigated headland where is very abundant in bushes and ups and downs of terrain, the values of observed F. P. concentration do not agree so well with the calculated values by the diffusion equation (Eq. 3) and Pasquill's formula as the hitherto results in the open flat region. But taking into account of the accuracy of the observed values, the availability of Pasquill's formula is comparatively recognized even in such a small scale region. 4) The values of F. P. concentration are extremely small at the downwind part of hill, the area of bushes and the valley. Accordingly, the atmospheric diffusion near the ground is much influenced by the effect of terrain and roughness of the ground surface.

Published
1971

4. APPLICATIONS OF A DIGITAL-COMPUTER SIMULATION OF A NEURAL NETWORK

Author

RAND CORP SANTA MONICA CALIF, Perkel,Donald H., RAND CORP SANTA MONICA CALIF, and Perkel,Donald H.

Abstract

The neuron model described was developed as an adjunct to experimental neurophysiological investigations. The model and its applications share a biological emphasis with the analog models of Harmon and Lewis and the digital-computer simulations of Farley, as distinguished from the emphasis on 'bionics' applications in the Perceptron., Presented at the Cybernetic Sciences Symposium. (2nd). The Los Angeles Invitational on Biophysics, at the University of Southern California, 13 Oct 64. Sponsored by ONR.

Published
1964

5. Lossless Compression of Medical Images Using a Dual Level DPCM with Context Adaptive Switching Neural Network Predictor

Author

R. S. Anand, Emjee Puthooran, and Shaktidev Mukherjee

Subjects
Lossless compression, General Computer Science, Artificial neural network, Pixel, Computer science, business.industry, Speech recognition, lossless image compression, Pattern recognition, Context (language use), computer.file_format, neural networks, lcsh:QA75.5-76.95, medical image, Computational Mathematics, Nonlinear system, Benchmark (computing), Entropy encoding, Artificial intelligence, lcsh:Electronic computers. Computer science, business, Pulse-code modulation, computer, dual level DPCM (DL-DPCM)
Abstract

A novel dual level differential pulse code modulation (DL-DPCM) is proposed for lossless compression of medical images. The DL-DPCM consists of a linear DPCM followed by a nonlinear DPCM namely, context adaptive switching neural network predictor (CAS-NNP). The CAS-NNP adaptively switches between three NN predictors based on the context texture of the predicted pixel in the image. Experiments on magnetic resonance (MR) images showed lower prediction error for the DL-DPCM compared to the GAP and the MED, which are used in benchmark algorithms CALIC and LOCO-I respectively. The overall improvement in data reduction after entropy coding the prediction error were 0.21 bpp (6.5%) compared to the CALIC and 0.40 bpp (11.7%) compared to the LOCO-I.

Published
1970

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