Now showing items 1-6 of 6
An open software architecture of neural networks: Neurosoft
Software architecture of generic distributed neural networks and its relevant information model have been developed. Principles of on-line architecture building training controlling (managing) and topological optimization ...
VLSI implementation of GRBF (Gaussian Radial Basis Function) networks
A GRBF network is designed for VLSI implementation. Building blocks of the network consist mainly of analog circuits: op-amp multiplier multiplying DAC (digital to analog converter) floating resistor summer and exponentiator. ...
Parameter quantization effects in Gaussian potential function neural networks
(World Scientific and Engineering Academy and Society, 2001)
In hardware implementations of Gaussian Potential Function Neural Networks (GPFNN) deviation from ideal network parameters is inevitable because of the techniques used for parameter storage and implementation of the functions ...
Abstraction in FPGA implementation of neural networks
(World Scientific and Engineering Academy and Society, 2008)
A model for FPGA implementation of multilayer perceptron neural networks is presented. The model tries to incorporate object oriented design principles in the analysis training and design of components using hardware ...
A systems software architecture for training neural fuzzy neural and genetic computational intelligent networks
A systems software architecture for training distributed neural fuzzy neural and genetic networks and their relevant information models have been developed. Principles of on-line architecture building training managing and ...
Fault-tolerant training of neural networks in the presence of MOS transistor mismatches
(IEEE-INST Electrical Electronics Engineers Inc, 2001)
Analog techniques are desirable for hardware implementation of neural networks due to their numerous advantages such as small size low power and high speed. However these advantages are often offset by the difficulty in ...