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» An adaptive learning algorithm for a neo fuzzy neuron
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NIPS
2003
13 years 9 months ago
Minimising Contrastive Divergence in Noisy, Mixed-mode VLSI Neurons
This paper presents VLSI circuits with continuous-valued probabilistic behaviour realized by injecting noise into each computing unit(neuron). Interconnecting the noisy neurons fo...
Hsin Chen, Patrice Fleury, Alan F. Murray
TFS
2011
194views Education» more  TFS 2011»
13 years 3 months ago
Top-Down Induction of Fuzzy Pattern Trees
Fuzzy pattern tree induction was recently introduced as a novel machine learning method for classification. Roughly speaking, a pattern tree is a hierarchical, tree-like structur...
R. Senge, Eyke Hüllermeier
ICCBR
2001
Springer
14 years 28 days ago
A Fuzzy-Rough Approach for Case Base Maintenance
Abstract. This paper proposes a fuzzy-rough method of maintaining CaseBased Reasoning (CBR) systems. The methodology is mainly based on the idea that a large case library can be tr...
Guoqing Cao, Simon C. K. Shiu, Xizhao Wang
ISCAS
2003
IEEE
117views Hardware» more  ISCAS 2003»
14 years 1 months ago
Learning temporal correlations in biologically-inspired aVLSI
Temporally-asymmetric Hebbian learning is a class of algorithms motivated by data from recent neurophysiology experiments. While traditional Hebbian learning rules use mean firin...
Adria Bofill-i-Petit, Alan F. Murray
CEC
2007
IEEE
14 years 2 months ago
Towards a generic control strategy for Evolutionary Algorithms: an adaptive fuzzy-learning approach
— This paper presents a new method to generalize strategies in order to control parameters of Evolutionary Algorithms (EAs). A learning process establishes the relationship betwe...
Jorge Maturana, Frédéric Saubion