This paper investigates the asymptotical stability problem for a class of neutral type neural networks with mixed time-varying delays. The system not only has time-varying discrete delay, but also distributed delay, which has never been discussed in ...
Neural networks : the official journal of the International Neural Network Society
Mar 30, 2015
It is a fundamental question how our brain performs a given motor task in a real-time fashion with the slow sensorimotor system. Computational theory proposed an influential idea of feed-forward control, but it has mainly treated the case that the mo...
To diagnose the malignancy in thyroid tumor, neural network approach is applied and the performances of thirteen batch learning algorithms are investigated on accuracy of the prediction. Therefore, a back propagation feed forward neural networks (BP ...
A statistical machine learning indicator, ACOustic, is proposed to evaluate the exploration behavior in the iterations of ant colony optimization algorithms. This idea is inspired by the behavior of some parasites in their mimicry to the queens' acou...
Community detection is a fundamental problem in the analysis of complex networks. Recently, many researchers have concentrated on the detection of overlapping communities, where a vertex may belong to more than one community. However, most current me...
Neural networks : the official journal of the International Neural Network Society
Mar 27, 2015
The urgent problem of impulsive moments which cannot be determined in advance brings new challenges beyond the conventional impulsive systems theory. In order to solve this problem, the novel concept of impulsive time window is proposed in this paper...
Non-invasively reconstructing the cardiac transmembrane potentials (TMPs) from body surface potentials can act as a regression problem. The support vector regression (SVR) method is often used to solve the regression problem, however the computationa...
We present prediction and variable importance (VIM) methods for longitudinal data sets containing continuous and binary exposures subject to missingness. We demonstrate the use of these methods for prognosis of medical outcomes of severe trauma patie...
KeBABS provides a powerful, flexible and easy to use framework for KE: rnel- B: ased A: nalysis of B: iological S: equences in R. It includes efficient implementations of the most important sequence kernels, also including variants that allow for tak...
Neural networks : the official journal of the International Neural Network Society
Mar 25, 2015
Biological systems are capable of learning that certain stimuli are valuable while ignoring the many that are not, and thus perform feature selection. In machine learning, one effective feature selection approach is the least absolute shrinkage and s...
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