Abstract A class of inertial neural networks (INNs) with reaction-diffusion terms and distributed delays is studied. The existence uniqueness the equilibrium point for considered system obtained by topological degree theory, a sufficient condition given to guarantee global exponential stability point. Finally, an example show effectiveness results in this paper.

Robust diffusion algorithms based on the maximum correntropy criterion(MCC) are developed to address the distributed networks estimation issue in impulsive(long-tailed) noise environments. The cost functions used in distributed network estimation are in general based on the mean square error (MSE) criterion, which is optimal only when the measurement noise is Gaussian. In non-Gaussian situation...

This letter proposes a sparse diffusion steepestdescent algorithm for one bit compressed sensing in wireless sensor networks. The approach exploits the diffusion strategy from distributed learning in the one bit compressed sensing framework. To estimate a common sparse vector cooperatively from only the sign of measurements, steepest-descent is used to minimize the suitable global and local con...

Diffusion processes are important models for many real-world phenomena, such as the spread of disease or rumors. We propose to study different aspects of diffusion processes in networks, focusing on designing efficient distributed algorithms for positive diffusion processes and good intervention strategies to control harmful diffusions. First, we design and analyze various distributed algorithm...

The theory of distributed detection is receiving a lot of attention. A common assumption used in previous studies is the conditional independence of the observations. In this paper, the optimization of local decision rules for distributed detection networks with correlated observations is considered. We focus on presenting the detection theory for parallel distributed detection networks with fi...

In this paper, a generalized reaction-diffusion model of Cohen Grossberg neural networks with time-varying and distributed delays is investigated. By employing analytic methods, inequality technique and M -matrix theory, some sufficient conditions ensuring the existence, uniqueness and global exponential stability of equilibrium point for Cohen-Grossberg neural networks with time-varying and di...

We envision that during the next decade the advances in technology will make sensor networks more powerful. Therefore, they will become part of a larger class of networks of embedded systems that have sufficient computing, communication, and energy resources to support distributed applications. The current software architectures and programming models are not suitable for these new computing en...

acceptance of information and information diffusion are the traditional concepts that can be reviewed from another point of view. acceptance of innovation and innovation diffusion model are starting points for analyzing these concepts. these concepts have an important role in designing systems and popularization of sciences. in addition, it is considerable in library and information studies whi...