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Stochastic Processes

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FPGA-Based Stochastic Echo State Networks for Time-Series Forecasting.

Computational intelligence and neuroscience
Hardware implementation of artificial neural networks (ANNs) allows exploiting the inherent parallelism of these systems. Nevertheless, they require a large amount of resources in terms of area and power dissipation. Recently, Reservoir Computing (RC...

A graph-based N-body approximation with application to stochastic neighbor embedding.

Neural networks : the official journal of the International Neural Network Society
We propose a novel approximation technique, bubble approximation (BA), for repulsion forces in an N-body problem, where attraction has a limited range and repulsion acts between all points. These kinds of systems occur frequently in dimension reducti...

Enhanced Logical Stochastic Resonance in Synthetic Genetic Networks.

IEEE transactions on neural networks and learning systems
In this brief, the concept of logical stochastic resonance is applied to implement the Set-Reset latch in a synthetic gene network derived from a bacteriophage λ . Clear Set-Reset latch operation is obtained when the network is only subjected to peri...

Enhancement of Spike-Timing-Dependent Plasticity in Spiking Neural Systems with Noise.

International journal of neural systems
Synaptic plasticity is widely recognized to support adaptable information processing in the brain. Spike-timing-dependent plasticity, one subtype of plasticity, can lead to synchronous spike propagation with temporal spiking coding information. Recen...

Distributed parameter estimation in unreliable sensor networks via broadcast gossip algorithms.

Neural networks : the official journal of the International Neural Network Society
In this paper, we present an asynchronous algorithm to estimate the unknown parameter under an unreliable network which allows new sensors to join and old sensors to leave, and can tolerate link failures. Each sensor has access to partially informati...

Firing rate dynamics in recurrent spiking neural networks with intrinsic and network heterogeneity.

Journal of computational neuroscience
Heterogeneity of neural attributes has recently gained a lot of attention and is increasing recognized as a crucial feature in neural processing. Despite its importance, this physiological feature has traditionally been neglected in theoretical studi...

Deep Neural Networks with Multistate Activation Functions.

Computational intelligence and neuroscience
We propose multistate activation functions (MSAFs) for deep neural networks (DNNs). These MSAFs are new kinds of activation functions which are capable of representing more than two states, including the N-order MSAFs and the symmetrical MSAF. DNNs w...

Dynamic Behavior of Artificial Hodgkin-Huxley Neuron Model Subject to Additive Noise.

IEEE transactions on cybernetics
Motivated by neuroscience discoveries during the last few years, many studies consider pulse-coupled neural networks with spike-timing as an essential component in information processing by the brain. There also exists some technical challenges while...

Synchronization of neural networks with stochastic perturbation via aperiodically intermittent control.

Neural networks : the official journal of the International Neural Network Society
In this paper, the synchronization problem for neural networks with stochastic perturbation is studied with intermittent control via adaptive aperiodicity. Under the framework of stochastic theory and Lyapunov stability method, we develop some techni...

Global neural dynamic surface tracking control of strict-feedback systems with application to hypersonic flight vehicle.

IEEE transactions on neural networks and learning systems
This paper studies both indirect and direct global neural control of strict-feedback systems in the presence of unknown dynamics, using the dynamic surface control (DSC) technique in a novel manner. A new switching mechanism is designed to combine an...