Neural Networks Simulation of Distributed SEIR System

Distributed, Event Driven Simulation of Spiking Neural Networks

We present the architecture of a simulator that is able to simulate large networks of spiking neurons using a distributed event driven simulation. Contrary to a time driven simulation, which is usually used to simulate spiking neural networks, our simulation needs less computational resources because of the low average activity of typical networks. The simulator is divided into a set of communi...

NSL/ASL: Distributed Simulation of Modular Neural Networks

As neural systems become large and complex, sophisticated tools are needed to support effective model development and efficient simulation processing. Initially, during model development, rich graphical interfaces linked to powerful programming languages and component libraries are the primary requirement. Later, during model simulation, processing efficiency is the primary concern. Workstation...

Cooperative Co-Evolving Neural Networks for Robosoccer Simulation

simulation and design of electronic processing circuit for restaurants e-procurement system

the poor orientation of the restaurants toward the information technology has yet many unsolved issues in regards to the customers. one of these problems which lead the appeal list of later, and have a negative impact on the prestige of the restaurant is the case when the later does not respond on time to the customers’ needs, and which causes their dissatisfaction. this issue is really sensiti...

Synthesis of recurrent neural networks for dynamical system simulation

We review several of the most widely used techniques for training recurrent neural networks to approximate dynamical systems, then describe a novel algorithm for this task. The algorithm is based on an earlier theoretical result that guarantees the quality of the network approximation. We show that a feedforward neural network can be trained on the vector-field representation of a given dynamic...