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Simple .m files, Basic NeuralNetworks study for Octave (or Matlab)
--> For a more detailed description check the README text under the 'Files' menu option :)
The project consists of a few very simple .m files for a Basic
NeuralNetworks study under Octave (or Matlab).
The idea is to provide a context for beginners that will allow to
develop neuralnetworks, while at the same time get to see and feel
the behavior of a basic neuralnetworks' functioning.
The code is completely open to be modified and may suit several scenarios.
The code commenting...
Cognity is an object-oriented neural network library for Java. It's goal is to provide easy-to-use, high level architecture for neural network computations along with reasonable performance.
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.
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Matlab Classification Toolbox contains implementations of the following classifiers: Naive Bayes, Gaussian, Gaussian Mixture Model, Decision Tree and NeuralNetworks. This toolbox allows users to compare classifiers across various data sets.
Neural network library for C++ applications in Windows and Linux.
Multi-Layer perceptron, radial-basis function networks and Hopfield networks are supported.
You can interface this with Matlab's Neural Network Toolbox using the Matlab Extensions Pack