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IWANN
2001
Springer
15 years 10 months ago
Learning Adaptive Parameters with Restricted Genetic Optimization Method
Abstract. Mechanisms for adapting models, filters, regulators and so on to changing properties of a system are of fundamental importance in many modern identification, estimation...
Santiago Garrido, Luis Moreno
ICIAP
2005
ACM
16 years 6 months ago
A Neural Adaptive Algorithm for Feature Selection and Classification of High Dimensionality Data
In this paper, we propose a novel method which involves neural adaptive techniques for identifying salient features and for classifying high dimensionality data. In particular a ne...
Elisabetta Binaghi, Ignazio Gallo, Mirco Boschetti...
NN
2002
Springer
107views Neural Networks» more  NN 2002»
15 years 5 months ago
Equivariant nonstationary source separation
Most of source separation methods focus on stationary sources, so higher-order statistics is necessary for successful separation, unless sources are temporally correlated. For non...
Seungjin Choi, Andrzej Cichocki, Shun-ichi Amari
FSKD
2005
Springer
180views Fuzzy Logic» more  FSKD 2005»
15 years 11 months ago
An Effective Feature Selection Scheme via Genetic Algorithm Using Mutual Information
Abstract. In the artificial neural networks (ANNs), feature selection is a wellresearched problem, which can improve the network performance and speed up the training of the networ...
Chunkai K. Zhang, Hong Hu
ISNN
2010
Springer
15 years 4 months ago
Particle Swarm Optimization Based Learning Method for Process Neural Networks
Abstract. This paper proposes a new learning method for process neural networks (PNNs) based on the Gaussian mixture functions and particle swarm optimization (PSO), called PSO-LM....
Kun Liu, Ying Tan, Xingui He