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» VLSI Implementation of Neural Networks
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110
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IJCNN
2007
IEEE
15 years 10 months ago
Theta Neuron Networks: Robustness to Noise in Embedded Applications
- In this paper, we train a one-layer Theta Neuron Network (TNN) to perform a Braitenberg obstacle avoidance algorithm on a Khepera robot. The Theta neuron model is more biological...
Sam McKennoch, Preethi Sundaradevan, Linda G. Bush...
150
Voted
IJON
2007
184views more  IJON 2007»
15 years 3 months ago
Convex incremental extreme learning machine
Unlike the conventional neural network theories and implementations, Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden n...
Guang-Bin Huang, Lei Chen
160
Voted
SBACPAD
2008
IEEE
249views Hardware» more  SBACPAD 2008»
15 years 10 months ago
Processing Neocognitron of Face Recognition on High Performance Environment Based on GPU with CUDA Architecture
This work presents an implementation of Neocognitron Neural Network, using a high performance computing architecture based on GPU (Graphics Processing Unit). Neocognitron is an ar...
Gustavo Poli, José Hiroki Saito, Joã...
166
Voted
EPS
1995
Springer
15 years 7 months ago
PANIC: A Parallel Evolutionary Rule Based System
PANIC (Parallelism And Neural networks In Classifier systems) is a parallel system to evolve behavioral strategies codified by sets of rules. It integrates several adaptive techni...
Antonella Giani, Fabrizio Baiardi, Antonina Starit...
128
Voted
IJCNN
2006
IEEE
15 years 9 months ago
Venn-like models of neo-cortex patches
— This work presents a new architecture of artificial neural networks – Venn Networks, which produce localized activations in a 2D map while executing simple cognitive tasks. T...
Fernando Buarque de Lima Neto, Philippe De Wilde