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» On computational limitations of neural network architectures
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ICNC
2005
Springer
14 years 29 days ago
Double Robustness Analysis for Determining Optimal Feedforward Neural Network Architecture
This paper incorporates robustness into neural network modeling and proposes a novel two-phase robustness analysis approach for determining the optimal feedforward neural network (...
Lean Yu, Kin Keung Lai, Shouyang Wang
FCCM
2000
IEEE
103views VLSI» more  FCCM 2000»
13 years 12 months ago
A Networked FPGA-Based Hardware Implementation of a Neural Network Application
This paper describes a networked FPGA-based implementation of the FAST (Flexible Adaptable-Size Topology) architecture, a Arti cial Neural Network (ANN) that dynamically adapts it...
Héctor Fabio Restrepo, Ralph Hoffmann, Andr...
NEUROSCIENCE
2001
Springer
13 years 12 months ago
Modularity and Specialized Learning: Mapping between Agent Architectures and Brain Organization
This volume is intended to help advance the field of artificial neural networks along the lines of complexity present in animal brains. In particular, we are interested in examin...
Joanna Bryson, Lynn Andrea Stein
ICIP
2003
IEEE
14 years 9 months ago
Non-linear 3D rendering workload prediction based on a combined fuzzy-neural network architecture for grid computing application
Although, computational Grid has been initially developed to solve large-scale scientific research problems, it is extended for commercial and industrial applications. An interest...
John K. Doulamis, Anastasios D. Doulamis
FPGA
2009
ACM
201views FPGA» more  FPGA 2009»
14 years 2 months ago
A high-performance FPGA architecture for restricted boltzmann machines
Despite the popularity and success of neural networks in research, the number of resulting commercial or industrial applications have been limited. A primary cause of this lack of...
Daniel L. Ly, Paul Chow