AIMC Topic: Markov Chains

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Stop! border ahead: Automatic detection of subthalamic exit during deep brain stimulation surgery.

Movement disorders : official journal of the Movement Disorder Society
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...

ACID: Association Correction for Imbalanced Data in GWAS.

IEEE/ACM transactions on computational biology and bioinformatics
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...

Mean-square exponential input-to-state stability of delayed Cohen-Grossberg neural networks with Markovian switching based on vector Lyapunov functions.

Neural networks : the official journal of the International Neural Network Society
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...

Synchronization of Markovian jumping inertial neural networks and its applications in image encryption.

Neural networks : the official journal of the International Neural Network Society
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...

Autoregressive-moving-average hidden Markov model for vision-based fall prediction-An application for walker robot.

Assistive technology : the official journal of RESNA
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...

An Ensemble Approach for Cognitive Fault Detection and Isolation in Sensor Networks.

International journal of neural systems
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...

Analysis of complex neural circuits with nonlinear multidimensional hidden state models.

Proceedings of the National Academy of Sciences of the United States of America
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...

Mapping Generative Models onto a Network of Digital Spiking Neurons.

IEEE transactions on biomedical circuits and systems
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...

A hierarchical model for integrating unsupervised generative embedding and empirical Bayes.

Journal of neuroscience methods
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...

Passivity analysis of uncertain stochastic neural networks with time-varying delays and Markovian jumping parameters.

Network (Bristol, England)
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...