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IJCNN
2006
IEEE
13 years 11 months ago
Divide and Conquer Strategies for MLP Training
— Over time, neural networks have proven to be extremely powerful tools for data exploration with the capability to discover previously unknown dependencies and relationships in ...
Smriti Bhagat, Dipti Deodhare
IJCNN
2006
IEEE
13 years 11 months ago
Generalization Improvement in Multi-Objective Learning
— Several heuristic methods have been suggested for improving the generalization capability in neural network learning, most of which are concerned with a single-objective (SO) l...
Lars Gräning, Yaochu Jin, Bernhard Sendhoff
IJCNN
2006
IEEE
13 years 11 months ago
Neural Network Model of Context-Dependent Neuronal Activity in Inferotemporal Cortex
— Neuronal activities related to context-dependent recall have been found in the monkey inferotemporal cortex. If we set the same task for an artificial neural network, however,...
Atsuo Suemitsu, Masahiko Morita
IJCNN
2006
IEEE
13 years 11 months ago
Effective Training Methods for Function Localization Neural Networks
— Inspired by Hebb’s cell assembly theory about how the brain worked, we have developed a function localization neural network (FLNN). The main part of a FLNN is structurally t...
Takafumi Sasakawa, Jinglu Hu, Katsunori Isono, Kot...
IJCNN
2006
IEEE
13 years 11 months ago
Computational Neurogenetic Modeling: A Methodology to Study Gene Interactions Underlying Neural Oscillations
—We present new results from Computational Neurogenetic Modeling to aid discoveries of complex gene interactions underlying oscillations in neural systems. Interactions of genes ...
Lubica Benuskova, Simei Gomes Wysoski, Nikola K. K...
IJCNN
2006
IEEE
13 years 11 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
IJCNN
2006
IEEE
13 years 11 months ago
Bi-directional Modularity to Learn Visual Servoing Tasks
— This paper shows the advantage of using neural network modularity over conventional learning schemes to approximate complex functions. Indeed, it is difficult for artificial ...
Gilles Hermann, Patrice Wira, Jean-Philippe Urban
ICICIC
2006
IEEE
13 years 11 months ago
Integration of Genetic Algorithm and Neural Network for Financial Early Warning System: An Example of Taiwanese Banking Industry
Genetic algorithm and neural network (GNN) are integrated to build a financial early warning system. An example of Taiwanese banking industry is discussed to test the hit ratio of...
Jih-Chang Hsieh, Pei-Chann Chang, Shih-Hsin Chen
NOLISP
2007
Springer
13 years 11 months ago
Word Recognition with a Hierarchical Neural Network
In this paper we propose a feedforward neural network for syllable recognition. The core of the recognition system is based on a hierarchical architecture initially developed for ...
Xavier Domont, Martin Heckmann, Heiko Wersing, Fra...

Publication
644views
13 years 11 months ago
Benchmarking and Comparing Encog, Neuroph and JOONE Neural Networks
In this article the author benchmarks Neuroph, JOONE and Encog. These are the three major open source frameworks for Java. Encog also has a .Net version. I will give all three fram...
Tahere Taheri