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» A Feedforward Neural Network based on Multi-Valued Neurons
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IJON
2000
86views more  IJON 2000»
13 years 7 months ago
Gain modulation of recurrent networks
Gain modulation is an important mechanism by which attentional and other inputs modify the amplitude of neuronal responses without changing their selectivity. Gain modulation has ...
Jian Zhang 0004, L. F. Abbott
RAS
2000
136views more  RAS 2000»
13 years 7 months ago
A comparative study of soft-computing methodologies in identification of robotic manipulators
This paper investigates the identification of nonlinear systems by utilizing soft-computing approaches. As the identification methods, Feedforward Neural Network architecture (FNN...
Mehmet Önder Efe, Okyay Kaynak
CSREAESA
2004
13 years 9 months ago
CMOS Implementation of Phase-Encoded Complex-Valued Artificial Neural Networks
- The model of a simple perceptron using phase-encoded inputs and complex-valued weights is presented. Multilayer two-input and three-input complex-valued neurons (CVNs) are implem...
Howard E. Michel, David Rancour, Sushanth Iringent...
DATE
2008
IEEE
134views Hardware» more  DATE 2008»
14 years 2 months ago
Scalable Architecture for on-Chip Neural Network Training using Swarm Intelligence
This paper presents a novel architecture for on-chip neural network training using particle swarm optimization (PSO). PSO is an evolutionary optimization algorithm with a growing ...
Amin Farmahini Farahani, Seid Mehdi Fakhraie, Saee...
IJCNN
2000
IEEE
13 years 12 months ago
Analog Hardware Implementation of the Random Neural Network Model
This paper presents a simple continuous analog hardware realization of the Random Neural Network (RNN) model. The proposed circuit uses the general principles resulting from the u...
Hossam Abdelbaki, Erol Gelenbe, Said E. El-Khamy