AIMC Topic: Stochastic Processes

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Sampled-Data Synchronization of Stochastic Markovian Jump Neural Networks With Time-Varying Delay.

IEEE transactions on neural networks and learning systems
In this article, sampled-data synchronization problem for stochastic Markovian jump neural networks (SMJNNs) with time-varying delay under aperiodic sampled-data control is considered. By constructing mode-dependent one-sided loop-based Lyapunov func...

Delay-Dependent Stability Analysis for Switched Stochastic Networks With Proportional Delay.

IEEE transactions on cybernetics
In this article, the issue of exponential stability (ES) is investigated for a class of switched stochastic neural networks (SSNNs) with proportional delay (PD). The key feature of PD is an unbounded time-varying delay. By considering the comparison ...

General Decay Stability for Nonautonomous Neutral Stochastic Systems With Time-Varying Delays and Markovian Switching.

IEEE transactions on cybernetics
A new type of asymptotic stability for nonlinear hybrid neutral stochastic systems with constant delays was investigated recently, where the criteria depended on the delays' sizes. Unfortunately, developed theory so far is not sufficient to deal with...

Stochastic Stability Analysis for Stochastic Coupled Oscillator Networks with Bidirectional Cross-Dispersal.

Computational intelligence and neuroscience
It is well known that stochastic coupled oscillator network (SCON) has been widely applied; however, there are few studies on SCON with bidirectional cross-dispersal (SCONBC). This paper intends to study stochastic stability for SCONBC. A new and sui...

The Synchronization Analysis of Cohen-Grossberg Stochastic Neural Networks with Inertial Terms.

Computational intelligence and neuroscience
The exponential synchronization (ES) of Cohen-Grossberg stochastic neural networks with inertial terms (CGSNNIs) is studied in this paper. It is investigated in two ways. The first way is using variable substitution to transform the system to another...

Practical Exponential Stability of Impulsive Stochastic Reaction-Diffusion Systems With Delays.

IEEE transactions on cybernetics
This article studies the practical exponential stability of impulsive stochastic reaction-diffusion systems (ISRDSs) with delays. First, a direct approach and the Lyapunov method are developed to investigate the p th moment practical exponential stab...

A framework for preparing a stochastic nonlinear integrate-and-fire model for integrated information theory.

Network (Bristol, England)
This paper presents a framework for spiking neural networks to be prepared for the Integrated Information Theory (IIT) analysis, using a stochastic nonlinear integrate-and-fire model. The model includes the crucial dynamics of the all-or-none law and...

A machine learning approach to identify stochastic resonance in human perceptual thresholds.

Journal of neuroscience methods
BACKGROUND: Stochastic resonance (SR) is achieved when a faint signal is improved with the addition of the appropriate amount of white noise. Perceptual thresholds are expected to follow a characteristic performance improvement curve as a function of...

A stroke detection and discrimination framework using broadband microwave scattering on stochastic models with deep learning.

Scientific reports
Stroke poses an immense public health burden and remains among the primary causes of death and disability worldwide. Emergent therapy is often precluded by late or indeterminate times of onset before initial clinical presentation. Rapid, mobile, safe...

DeepCME: A deep learning framework for computing solution statistics of the chemical master equation.

PLoS computational biology
Stochastic models of biomolecular reaction networks are commonly employed in systems and synthetic biology to study the effects of stochastic fluctuations emanating from reactions involving species with low copy-numbers. For such models, the Kolmogor...