Neural network software

The primary purpose of this type of software is, through simulation, to gain a better understanding of the behavior and the properties of neural networks.

Today in the study of artificial neural networks, simulators have largely been replaced by more general component based development environments as research platforms.

In such simulators the physical biological and chemical properties of neural tissue, as well as the electromagnetic impulses between the neurons are studied.

Commonly used biological network simulators include Neuron, GENESIS, NEST and Brian.

Unlike the more general development environments, data analysis simulators use a relatively simple static neural network that can be configured.

A majority of the data analysis simulators on the market use backpropagating networks or self-organizing maps as their core.

The original PDP software did not require any programming skills, which led to its adoption by a wide variety of researchers in diverse fields.

[4] This was a return to the idea of providing a small, user-friendly, simulator that was designed with the novice in mind.

Basic Prop is a self-contained application, distributed as a platform neutral JAR file, that provides much of the same simple functionality as tLearn.

Free open source component based environments include Encog and Neuroph.

There are also many programming libraries that contain neural network functionality and that can be used in custom implementations (such as TensorFlow, Theano, etc., typically providing bindings to languages such as Python, C++, Java).