Olsoft Neural Network Library


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Olsoft Neural Network Library  v.1.0

OLSOFT Neural Network Library is the class to create, learn and use Back Propagation neural networks and SOFM (Self-Organizing Feature Map). The library makes integration of neural networks' functionality into your own applications easy and seamless.

Sharky Neural Network 0.9.Beta  v.1.0

Neural network classification results live view (like a movie). Free software for playing with neural networks classification. Major features * Easy, ready to play with. * Live view. * Many network architectures. * Different shapes of training data sets.





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Neural Network Component (ActiveX)  v.1.0

Artificial Neural System Component is designed for researchers in the fields of machine learning, it can be used to construct Back Propagation Neural Network and to train it with provided samples, then finally recall it with appropriate data.

This ...

Artificial Neural Network  v.1.0

Create artificial neural networks. Artificial Neural Network demonstrate artificial intelligence. Taking advantage of serialization, there are two parts of the network. The actual network, and then training data. The C# version of the Artificial Neural ...

Magi Network Library  v.1.1

The Magi Systems Network Library is a 100% Java-based network library that can be used as the foundation of a network based Java application, where there is a central multi-threaded server and multiple clients connecting remotely, either across a local-area ...

Amethyst Network Library  v.0.1.2

The Amethyst Network Library is a Java-based network library developed specifically for the Java platform. This library can be used within any Java application to streamline and abstract the I/O of Java Sockets.

Geeks Artificial Neural Network  v.1.4

Geeks Artificial Neural Network (G.A.N.N) is an open source project that started with the philosophy of being a new more advanced A.N.N that works as a platform for other applications. In other words, G.A.N.N should be considered as a "Black Box".

Interactive Neural Network Simulator  v.1.0

iSNS is an interactive neural network simulator written in Java/Java3D. The program is intended to be used in lessons of Neural Networks. The program was developed by students as the software project at Charles University in Prague.

Java Neural Network Framework Neuroph  v.2.5.1

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.

Simple Neural ARchitecture LIbrary  v.1.0

SNARLI (Simple Neural ARchitecture LIbrary) is a Java package containing a back-prop layer class and classes for the Self-Organizing Map and Incremental Growing Grid. The back-prop class supports sigma-pi connections and back-prop-through-time.

Neuroph  v.2.5.1 RC 2

Neuroph is Java framework for neural network development. It contains well designed, open source Java library with small number of basic classes which correspond to basic NN concepts. Also has nice GUI neural network editor to quickly create Java neural ...

RNNLIB  v.b

RNNLIB is a recurrent neural network library for sequence learning problems. Applicable to most types of spatiotemporal data, it has proven particularly effective for speech and handwriting recognition.

Neural Creator  v.1.0

Neural Creator is our visually based neural network development system that can be trained to perform pattern matching, feature recognition or make predictions on noisy or fuzzy data. It has an easy to use interface and comes with example projects and ...

EasyNN-plus

EasyNN-plus is a neural network system for Microsoft Windows. It makes the creation of neural networks easy. It allows the user to produce multilayer neural networks from a grid or from text files and images. The user can produce training, validating ...

SwingNN

Your data is imported into a grid and used to train a neural network. The input values are forced to swing beyond their limits. The output values are forecasted by the neural network. A new neural network is created using the new inputs and forecasted ...

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