Search Results for "network simulation"

Beyond its much publicized success in attaining superhuman level at games such as Chess and Go, DeepMind's AlphaZero algorithm illustrates a more general methodology of combining learning and search to explore large combinatorial spaces effectively. We believe that this methodology can have exciting applications in many different research areas. Because AlphaZero is resource-hungry, successful open-source implementations (such as Leela Zero) are written in low-level languages (such as C++)...

... and methods or to connect an external simulation tool. The latest version in development is hosted at https://github.com/smartgrids-aau/Frevo

Neuroph is lightweight Java Neural Network Framework which can be used to develop common neural network architectures. Small number of basic classes which correspond to basic NN concepts, and GUI editor makes it easy to learn and use.

This project includes the implementation of a neural network MLP, RBF, SOM and Hopfield networks in several popular programming languages. The project also includes examples of the use of neural networks as function approximation and time series prediction. Includes a special program makes it easy to test neural network based on training data and the optimization of the network.

... sensory activity, etc. NeuraNEP handles microthread scheduling, synchronization, distribution and communication. This project is a fork of SpikeOS (sourceforge.net/projects/spikeos) and represents a major update to that code base, including a scripting interface and low-level rewrite of several components. SpikeOS was oriented towards computational modeling. NeuraNEP is oriented toward neural network research.

A parallel-programming framework for concurrently running large numbers of small autonomous jobs, or microthreads, across multiple cores in a CPU or CPUs in a cluster. Each microthread is conceptually similar to a task in Ada and it is much lighter weight than an operating system thread. SpikeOS was designed to handle millions of microthreads, for example in a neural network hosting millions of spiking model neurons. SpikeOS handles microthread scheduling, synchronization, distribution...

NeMo is a high-performance spiking neural network simulator which simulates networks of Izhikevich neurons on CUDA-enabled GPUs. NeMo is a C++ class library, with additional interfaces for pure C, Python, and Matlab.

SPLITNEURON is a completely new approach to large-scale, biologically plausible, neural-network simulation library based on data structures and methods directly coded into database and conceived to explicitly share load on multiple machines.

Neural Network class library: Its a C/C++ implementation that provides following three neural architecture - Feed-forward network, Radial Basis function network, multi-layer perceptron and Self-Organizing Maps.

The DAMNED simulator is a Distributed And Multithreaded Neural Event-Driven simulation framework designed for Distributed Discrete Event Simulations, actually well suited for Large Scale Spiking Neural Network simulations.

TIKAPP is becoming a collection of tools for simulation of neural networks. The first available part is an ANSI-C++ library with support for backpropation networks.

Cluster Networks are a new style of neural simulation / neural network modeling, that models networks of neural populations ("clusters") that transform and transmit information using precisely-timed, graded bursts ("pulses" or "volleys") of firing.

LiNNS is not just a Neural Network Simulator, but a Neural Network System - a framework which covers the full lifecycle of a neural network, from design and research till usage in an external application.