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Field-programmable gate arrays (FPGAs) can provide an efficient programmable resource for implementing hardware-based spiking neural networks (SNN). In this paper we present a hardware-software design that makes it possible to simulate large-scale (2 million neurons) biologically plausible SNNs on an FPGA-based system. We have chosen three SNN models from the various models available in the literature,...
The Hind marsh-Rose (HR) Neuron not only contained the features of cell biological physical model, but also included the traits of non-linear dynamical system model. The paper analyzed the HR model by computing manifold. It computed the equilibria, simulated the bifurcation phenomenon of the parameters, estimated the unstable local manifold and computed the global manifold using the angle constraint...
This paper firstly examines the traditional vehicle styling evaluation methods and issues, and then presents a new approach which uses ANN (artificial neural network) to build an expert system for bus styling evaluation. It describes the key technical issues of quasi-three-dimensional bus styling evaluation expert system from data collection, graphical pre-processing, graphics feature extraction,...
Due to their adverse health effects and their abundance in urban areas, diesel exhaust particles (DEP) have been of great concern in the past years. An experiment was carried out on a direct injection, turbocharged diesel engine to investigate the number emission characteristics of particles. Furthermore, an artificial neural network (ANN) was used to establish an emission model of the diesel engine...
The artificial neural network (ANN) method is used to study the macroscopic model of an actual water distribution system. For the first time, the Ant Colony Optimization (ACO) algorithm is implemented to optimize the node numbers of the hidden layers in the ANN model. The ANN model contains two hidden layers with a maximum of 64 nodes per layer. Each node number in the hidden layers is transformed...
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