Movement disorders : official journal of the Movement Disorder Society
Oct 6, 2016
BACKGROUND: Microelectrode recordings along preplanned trajectories are often used for accurate definition of the subthalamic nucleus (STN) borders during deep brain stimulation (DBS) surgery for Parkinson's disease. Usually, the demarcation of the S...
IEEE/ACM transactions on computational biology and bioinformatics
Sep 13, 2016
Genome-wide association study (GWAS) has been widely witnessed as a powerful tool for revealing suspicious loci from various diseases. However, real world GWAS tasks always suffer from the data imbalance problem of sufficient control samples and limi...
Neural networks : the official journal of the International Neural Network Society
Aug 24, 2016
This paper studies the mean-square exponential input-to-state stability of delayed Cohen-Grossberg neural networks with Markovian switching. By using the vector Lyapunov function and property of M-matrix, two generalized Halanay inequalities are esta...
Neural networks : the official journal of the International Neural Network Society
Aug 17, 2016
This study is mainly concerned with the problem on synchronization criteria for Markovian jumping time delayed bidirectional associative memory neural networks and their applications in secure image communications. Based on the variable transformatio...
Assistive technology : the official journal of RESNA
Jul 22, 2016
Population aging of the societies requires providing the elderly with safe and dependable assistive technologies in daily life activities. Improving the fall detection algorithms can play a major role in achieving this goal. This article proposes a r...
International journal of neural systems
Jun 26, 2016
Cognitive fault detection and diagnosis systems are systems able to provide timely information about possibly occurring faults without requiring any a priori knowledge about the process generating the data or the possible faults. This ability is cruc...
Proceedings of the National Academy of Sciences of the United States of America
May 24, 2016
A universal need in understanding complex networks is the identification of individual information channels and their mutual interactions under different conditions. In neuroscience, our premier example, networks made up of billions of nodes dynamica...
IEEE transactions on biomedical circuits and systems
May 18, 2016
Stochastic neural networks such as Restricted Boltzmann Machines (RBMs) have been successfully used in applications ranging from speech recognition to image classification, and are particularly interesting because of their potential for generative ta...
BACKGROUND: Generative models of neuroimaging data, such as dynamic causal models (DCMs), are commonly used for inferring effective connectivity from individual subject data. Recently introduced "generative embedding" approaches have used DCM-based c...
This paper investigates the problem of robust passivity of uncertain stochastic neural networks with time-varying delays and Markovian jumping parameters. To reflect most of the dynamical behaviors of the system, both parameter uncertainties and stoc...
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