Wrapper-based feature selection is attractive because wrapper methods are able to optimize the features they select to the specific learning algorithm. Unfortunately, wrapper met...
— We have found a more general formulation of the REINFORCE learning principle which had been proposed by R. J. Williams for the case of artificial neural networks with stochast...
—In the past decade, artificial neural networks (ANNs) have been widely applied to the engineering problems with a complicated system. ANNs are becoming an important alternative ...
Deaho Cha, Michael Blumenstein, Hong Zhang, Dong-S...
— We describe an implementation of Gabor-type filters on field programmable gate arrays using the cellular neural network (CNN) architecture. The CNN template depends upon the ...
Ocean Y. H. Cheung, Philip Heng Wai Leong, Eric K....
— We present a novel network of oscillatory units, whose behavior is described by the amplitude and phase of oscillations. While building on previous work, the system presented i...
A. Ravishankar Rao, Guillermo A. Cecchi, Charles C...
Abstract— Supervised learning rules for spiking neural networks are currently only able to use time-to-first-spike coding and are plagued by very irregular learning curves due t...
—Computational models of development aim to describe the mechanisms that underlie the acquisition of new skills or the emergence of new capabilities. The strength of a model is j...
— Outliers refer to “minority” data that are different from most other data. They usually disturb data mining process. But, sometimes they provide valuable information. Thus,...
— Adaptive filtering is normally utilized to estimate system states or outputs from continuous valued observations, and it is of limited use when the observations are discrete e...