Also, you can drive the network from a python program. A custom network compiler can be implemented to encode the network for your own specialized hardware. A variety of models can be implemented, including Backpropagation Networks, Elman Networks, Jordan Networks, Functional Link Networks, Counterpropagation Networks, Multidirectional Associative Memories, Hopfield Memories, Markov Chains, Fuzzy Neural Systems, Recurrent Networks, and any variation or combination of these. Any application that can be expressed with a discrete-time connectionist model is within the scope of Neural Python. Current Status The C kernel and Python interface are complete.
Several extensions have yet to be written.
Many IDE features need to be implemented. XML file formats need work. Preliminary documentation Neural Network Links Neural Networks in Hardware - Excellent overview. Who is using neural nets and why, hardware vs. software, etc. Neural Networks at PPNL - Excellent site.