A neural correlate of parametric working memory is a stimulus-specific rise in neuron firing rate that persists long after the stimulus is removed. Network models with local excitation and broad inhibition support persistent neural activity, linking network architecture and parametric working memory. Cortical neurons receive noisy input fluctuations that cause persistent activity to diffusively...

This paper proposes an unconventional anomaly detection approach that provides digital instrumentation and control (I&C) systems in a nuclear power plant (NPP) with the capability to probabilistically discern between legitimate protocol frames and attack frames. The stochastic activity network (SAN) formalism is used to model the fusion of protocol activity in each digital I&C system and the op...

The activity of a neuron subjected to an input of many small excitatory and inhibitory pulses is analysed. The theoretical model consists of a linear or nonlinear first order system followed by a threshold. Diffusion equations for the transition probability density of the somatic potential are derived. Analytical results for the stationary activity include expressions for the stationary distrib...

malting is a complex biotechnological process that includes steeping; germination and drying of cereal grains under controlled conditions of temperature and humidity. in this research malting process parameters were predict by modular neural network with different activation function included, logsig-logsig, tanh-tanh, logsigtanh, logsig-identity and tanh-identity. steeping time (x1) and germin...

9 Spike patterns are among the most common electrophysiological descriptors of neuron types. Surprisingly, it is not clear how the diversity in firing patterns of the neurons in a network affects its activity dynamics. Here, we introduce the state-dependent stochastic bursting neuron model allowing for a change in its firing patterns independent of changes in its input-output firing rate relati...