Results 141 to 150 of about 389,041 (190)
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Microelectronics Reliability, 1991
Abstract A computer program is written to simulate the neural network realizing the discrete-time Markov model of the TMR system. The results obtained, highlighted in this paper, support the theory of the new approach to reliability and fault-tolerance analysis using neural networks.
C.A. Goben, M. Suliman, M.A. Manzoul
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Abstract A computer program is written to simulate the neural network realizing the discrete-time Markov model of the TMR system. The results obtained, highlighted in this paper, support the theory of the new approach to reliability and fault-tolerance analysis using neural networks.
C.A. Goben, M. Suliman, M.A. Manzoul
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Explainable neural networks that simulate reasoning
Nature Computational Science, 2021The success of deep neural networks suggests that cognition may emerge from indecipherable patterns of distributed neural activity. Yet these networks are pattern-matching black boxes that cannot simulate higher cognitive functions and lack numerous neurobiological features.
Paul J. Blazek, Milo M. Lin
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1991
Large scale implementations of neural networks arc presently not available. However, serial and parallel computers have been used to simulate neural networks [2, 5]. We describe algorithms for simulating the neural network on a serial computer and discuss possible implementations of these algorithms on parallel computers.
Srimat T. Chakradhar +2 more
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Large scale implementations of neural networks arc presently not available. However, serial and parallel computers have been used to simulate neural networks [2, 5]. We describe algorithms for simulating the neural network on a serial computer and discuss possible implementations of these algorithms on parallel computers.
Srimat T. Chakradhar +2 more
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Artificial Neural Network Simulation
2021This chapter discusses the necessity to formulate artificial neural network (ANN) simulation of the concerned field data. Multilayer feed forward topology is decided for the network. MATLAB software is used for training the network for response variable and to calculate percentage error plot for prediction for the network for the concerned variable ...
Pramod Belkhode +3 more
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Neural network software simulation
International Journal of Computer Mathematics, 1999The software implementations of the systolic array simulator that closely matches the hardware and software designs of [KaEv 96] and [EvKa 99] are presented. In addition to the general operation of the software [Ka 99], several applications are implemented in order to show that the designed architecture is capable of successfully carrying out neural ...
A. J. Kane, D. J. Evans
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1993
The aim of this chapter is to give an overview of existing neural network simulators, their performance, and hardware requirements. The intention of Artificial Neural Network (ANN) Simulators is to provide the possibility of testing the performance of network types, architectures, initialisations, algorithms and parameter sets.
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The aim of this chapter is to give an overview of existing neural network simulators, their performance, and hardware requirements. The intention of Artificial Neural Network (ANN) Simulators is to provide the possibility of testing the performance of network types, architectures, initialisations, algorithms and parameter sets.
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Auditory Neural Pathway Simulation
2017 IEEE International Conference on Rebooting Computing (ICRC), 2017We describe an effort to simulate the neural pathway from the inner ear (cochlea) to the primary auditory cortex in the brain. The human cochlea contains sensory cells (inner hair cells), which respond to the mechanical motion of traveling waves that sweep along the basilar membrane.
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Simulating spiking neural networks on GPU
Network: Computation in Neural Systems, 2012Modern graphics cards contain hundreds of cores that can be programmed for intensive calculations. They are beginning to be used for spiking neural network simulations. The goal is to make parallel simulation of spiking neural networks available to a large audience, without the requirements of a cluster. We review the ongoing efforts towards this goal,
Romain, Brette, Dan F M, Goodman
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DAPHNE: DATA PARALLELISM NEURAL NETWORK SIMULATOR
International Journal of Modern Physics C, 1993In this paper we describe the guideline of Daphne, a parallel simulator for supervised recurrent neural networks trained by Backpropagation through time. The simulator has a modular structure, based on a parallel training kernel running on the CM-2 Connection Machine.
FRASCONI, PAOLO, GORI M, SODA, GIOVANNI
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Constructing Realistic Neural Simulations with GENESIS
2007The GEneral NEural SImulation System (GENESIS) is an open source simulation platform for realistic modeling of systems ranging from subcellular components and biochemical reactions to detailed models of single neurons, simulations of large networks of realistic neurons, and systems-level models. The graphical interface XODUS permits the construction of
James M, Bower, David, Beeman
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