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» Evolvable Hardware for Generalized Neural Networks
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AI
2002
Springer
13 years 7 months ago
Ensembling neural networks: Many could be better than all
Neural network ensemble is a learning paradigm where many neural networks are jointly used to solve a problem. In this paper, the relationship between the ensemble and its compone...
Zhi-Hua Zhou, Jianxin Wu, Wei Tang
EWLR
1999
Springer
13 years 12 months ago
Toward Seamless Transfer from Simulated to Real Worlds: A Dynamically-Rearranging Neural Network Approach
In the field of evolutionary robotics artificial neural networks are often used to construct controllers for autonomous agents, because they have useful properties such as the ab...
Peter Eggenberger, Akio Ishiguro, Seiji Tokura, To...
GECCO
2005
Springer
175views Optimization» more  GECCO 2005»
14 years 1 months ago
Nonlinear feature extraction using a neuro genetic hybrid
Feature extraction is a process that extracts salient features from observed variables. It is considered a promising alternative to overcome the problems of weight and structure o...
Yung-Keun Kwon, Byung Ro Moon
IJCNN
2000
IEEE
14 years 2 days ago
Hardware Implementation of a PCA Learning Network by an Asynchronous PDM Digital Circuit
We have fabricated a PCA (Principal Component Analysis) learning network in a FPGA (Field Programmable Gate Array) by using an asynchronous PDM (Pulse Density Modulation) digital ...
Yuzo Hirai, Kuninori Nishizawa
IWANN
2009
Springer
14 years 2 months ago
Development of Neural Network Structure with Biological Mechanisms
We present an evolving neural network model in which synapses appear and disappear stochastically according to bio-inspired probabilities. These are in general nonlinear functions ...
Samuel Johnson, Joaquín Marro, Jorge F. Mej...