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IJCSS
2007
122views more  IJCSS 2007»
13 years 10 months ago
Artificial Neural Network Type Learning with Single Multiplicative Spiking Neuron
In this paper, learning algorithm for a single multiplicative spiking neuron (MSN) is proposed and tested for various applications where a multilayer perceptron (MLP) neural netwo...
Deepak Mishra, Abhishek Yadav, Sudipta Ray, Prem K...
OR
2006
Springer
13 years 10 months ago
Financial forecasting through unsupervised clustering and neural networks
In this paper, we review our work on a time series forecasting methodology based on the combination of unsupervised clustering and artificial neural networks. To address noise and...
Nicos G. Pavlidis, Vassilis P. Plagianakos, Dimitr...
NPL
2006
172views more  NPL 2006»
13 years 10 months ago
Adapting RBF Neural Networks to Multi-Instance Learning
In multi-instance learning, the training examples are bags composed of instances without labels, and the task is to predict the labels of unseen bags through analyzing the training...
Min-Ling Zhang, Zhi-Hua Zhou
NPL
2006
113views more  NPL 2006»
13 years 10 months ago
A Back-propagation Neural Network Landmine Detector Using the Delta-technique and S-statistic
Landmines are a major problem facing the world today; there are millions of these deadly weapons still buried in various countries around the world. Humanitarian organizations dedi...
Taskin Koçak, Matthew Draper
NN
2006
Springer
105views Neural Networks» more  NN 2006»
13 years 10 months ago
Unfolding preprocessing for meaningful time series clustering
Clustering methods are commonly applied to time series, either as a preprocessing stage for other methods or in their own right. In this paper it is explained why time series clus...
Geoffroy Simon, John Aldo Lee, Michel Verleysen
NN
2006
Springer
100views Neural Networks» more  NN 2006»
13 years 10 months ago
Neural voting machines
In theories of cognition that view the mind as a system of interacting agents, there must be mechanisms for aggregate decision-making, such as voting. Here we show that certain vo...
Whitman Richards, H. Sebastian Seung, Galen Pickar...
NN
2006
Springer
13 years 10 months ago
Granular self-organizing map (grSOM) for structure identification
Vassilis G. Kaburlasos, Stelios E. Papadakis
NN
2006
Springer
13 years 10 months ago
On the social psychology of modelling
Bernhard Hommel
NN
2006
Springer
146views Neural Networks» more  NN 2006»
13 years 10 months ago
Comparison of relevance learning vector quantization with other metric adaptive classification methods
The paper deals with the concept of relevance learning in learning vector quantization and classification. Recent machine learning approaches with the ability of metric adaptation...
Thomas Villmann, Frank-Michael Schleif, Barbara Ha...
NN
2006
Springer
13 years 10 months ago
Pre-attentive visual selection
Zhaoping Li, Peter Dayan