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ESANN
2006
15 years 2 months ago
Optimal design of hierarchical wavelet networks for time-series forecasting
The purpose of this study is to identify the Hierarchical Wavelet Neural Networks (HWNN) and select important input features for each sub-wavelet neural network automatically. Base...
Yuehui Chen, Bo Yang, Ajith Abraham
141
Voted
NN
2000
Springer
170views Neural Networks» more  NN 2000»
15 years 1 months ago
Synthetic brain imaging: grasping, mirror neurons and imitation
The article contributes to the quest to relate global data on brain and behavior (e.g. from PET, Positron Emission Tomography, and fMRI, functional Magnetic Resonance Imaging) to ...
Michael A. Arbib, Aude Billard, Marco Iacoboni, Er...
AINA
2010
IEEE
15 years 16 days ago
Compensation of Sensors Nonlinearity with Neural Networks
—This paper describes a method of linearizing the nonlinear characteristics of many sensors using an embedded neural network. The proposed method allows for complex neural networ...
Nicholas J. Cotton, Bogdan M. Wilamowski
ICCL
1992
IEEE
15 years 5 months ago
Multiparadigm data structures in Leda
Multiparadigm programming is a term used to describe a style of software development that makes use of facilities originally designed in support of a number of di erent programmin...
Timothy A. Budd
123
Voted
ICTAI
2007
IEEE
15 years 7 months ago
CompoNet: Programmatically Embedding Neural Networks into AI Applications as Software Components
The provision of embedding neural networks into software applications can enable variety of Artificial Intelligence systems for individual users as well as organizations. Previous...
Uzair Ahmad, Andrey Gavrilov, Sungyoung Lee, Young...