Parallel Simulation of Pulse Coded Neural Networks

Efficient Parallel Simulation of Pulse-Coded Neural Networks (PCNN)

An accelerator for neural networks with pulse-coded model neurons

The labeling of features by synchronization of spikes seems to be a very efficient encoding scheme for a visual system. Simulation of a vision system with millions of pulse-coded model neurons, however, is almost impossible on the base of available processors including parallel processors and neurocomputers. A "one-to-one" silicon implementation of pulse-coded model neurons suffers from communi...

MASPINN: Novel Concepts for a Neuro-Accelerator for Spiking Neural Networks

We present the basic architecture of a Memory Optimized Accelerator for Spiking Neural Networks (MASPINN). The accelerator architecture exploits two novel concepts for an efficient computation of spiking neural networks: weight caching and a compressed memory organization. These concepts allow a further parallelization in processing and reduce bandwidth requirements on accelerator’s components....

Distribution Systems Reconfiguration Using Pattern Recognizer Neural Networks

A novel intelligent neural optimizer with two objective functions is designed for electrical distribution systems. The presented method is faster than alternative optimization methods and is comparable with the most powerful and precise ones. This optimizer is much smaller than similar neural systems. In this work, two intelligent estimators are designed, a load flow program is coded, and a spe...

Bio - Inspired Arti cial Neural Networks

A uniied model for the simulation of artiicial and biology-oriented neural networks is presented. It supports all rate-coded and also many pulse-coded neural network models. The focus of the paper is on the special requirements for the simulation of neural networks built from neurons modelled by a single compartment. The derived uniied neural network model represents a basis for the design of a...