NeuroSolutions v5.05

Category Intelligent Software>Neural Network Systems/Tools

Abstract NeuroSolutions is a highly graphical neural network (NN) development tool. Product combines a modular, icon-based network design interface with an implementation of advanced learning procedures and genetic optimization. The result is an advanced environment for designing neural networks for research and for solving real-world problems.

Product features/capabilities include:

Temporal Neural Networks - NeuroSolutions is one of the few neural network development tools to fully support backpropagation through time (BPTT). Instead of mapping a static input to a static output, BPTT maps a series of inputs to a series of outputs. This provides the ability to solve temporal problems by extracting how data changes over time. Examples of temporal problems are digital signal processing, speech recognition, and time-series prediction.

User-defined Neural Topologies - NeuroSolutions is based on the concept that neural networks can be broken down into a fundamental set of neural components. Individually these components are relatively simplistic, but several components connected together can result in networks capable of solving very complex problems. The network construction wizards will connect these components for you based on your specifications. However, once the network is built you can arbitrarily change interconnections and/or add in new components. In other words, a virtually infinite number of neural models are possible!

User-defined Neural Components - The Developers and Developers Lite levels allow you to integrate your own algorithms into NeuroSolutions through dynamic link libraries (DLLs). Every NeuroSolutions component implements a function conforming to a simple protocol in C. To add a new component you simply modify the template function for the base component and compile the code into a DLL -- all directly from NeuroSolutions! Note: this feature requires that Microsoft Visual C++ (version 5.0 or higher) be installed on the same machine.

C++ Code Generation - An application developer can integrate a NeuroSolutions neural network into their application by generating a DLL with the Custom Solution Wizard or by generating the C++ source code for the network using the Professional or Developers level of NeuroSolutions. The generated network can be trained before hand within the graphical design environment of NeuroSolutions or from within your C++ application.

Product ships with the libraries for the Microsoft Visual C++ (5.0 and above) and Borland Builder (3.0 and above) compilers. NeuroDimension makes the source code for the entire object library available as a separate product called the Source Code License for developers who wish to use a different Windows compiler or a compiler on a different operating system entirely, such as UNIX.

Extensive Probing Capabilities - Probes provide you with real-time access to all internal network variables, such as: 1) Inputs/Outputs; 2) Weights; 3) Errors; 4) Hidden States; 5) Gradients; 6) Sensitivities. The probe components are inherently modular; the way you view the data is independent of what the data represents. All network data are reported through a common protocol, and all NeuroSolutions probes understand this protocol. This provides you with access to all internal variables, along with a variety of ways to visualize them.

Genetic Optimization - The Users level of NeuroSolutions and above include Genetic Optimization. Genetic Optimization allows you to optimize virtually any parameter in a neural network to produce the lowest error. For example, the number of hidden units, the learning rates, and the input selection can all be optimized to improve the network performance. Individual weights used in the NN can even be updated through Genetic Optimization as an alternative to traditional training methods.

Sensitivity Analysis - After training a NN, you may want to know the effect that each of the network inputs is having on the network output. The sensitivity analysis feature of NeuroSolutions can be used to perform this function. Sensitivity analysis is a method for extracting the cause and effect relationship between the inputs and outputs of the network.

Exemplar Weighting - Classification problems often do Not have an equal number of training exemplars (samples) for each class. For example, you may have a neural network application that detects the occurrence of cancer from clinical test data. The training data for this problem may contain 99 exemplars classified as non-cancerous for every one exemplar classified as cancerous. A standard neural network would most often train itself to classify all exemplars as non- cancerous so that it would be 99% correct. Since the goal is to detect the existence of cancer, this is a problem.

One way to overcome this problem would be to throw away most of the training exemplars so that there would be an equal number for each class. This would drastically reduce the amount of training data, and likely result in a network with poor generalization.

NeuroSolutions provides a better solution using a method called exemplar weighting. For the example above, each of the cancerous training exemplars would have 99 times more weight during the backpropagation procedure than the non cancerous exemplars. This balancing of the training data will most likely result in a system that does a much better job of detecting the cancerous cases.

Macros - Product provides a comprehensive macro language, which allows the user to record a sequence of operations and store them as a program. Any action that can be performed using the mouse and keyboard can be duplicated with a macro statement. This feature gives the user flexibility in constructing, editing, and running neural networks.

OLE Automation - NeuroSolutions is a fully compliant OLE Automation Server. This means that NeuroSolutions can receive control messages from OLE Automation Controllers, such as Visual C++, Visual Basic, Microsoft Excel, Microsoft Access, and Delphi.

Network Construction Wizards - NeuroSolutions has three (3) separate wizards that you can use to automatically build a neural network to your design specifications:

1) Data Manager - allows you to import data from Access, Excel or text files and do various preprocessing and data analysis operations. From there, you can load the data directly into a NeuroSolutions Breadboard or use the data to create a new neural network.

2) NeuralExpert - The NeuralExpert centers the design specifications around the type of problem you wish the neural network to solve (Classification, Prediction, Function Approximation or Clustering). Given this problem type and the size of your data set, the NeuralExpert intelligently selects the neural network size and architecture that will most likely produce a good solution.

3) NeuralBuilder - The NeuralBuilder centers the design specifications around the specific neural network architecture you wish to have built. Some of the most common architectures include:

a) Multilayer Perceptron (MLP); b) Generalized Feedforward; c) Modular; d) Jordan/Elman; e) Principal Component Analysis (PCA); f) Radial Basis Function (RBF); g) General Regression Neural Network (GRNN); h) Probabilistic Neural Network (PNN); i) Self-Organizing Map (SOM); j) Time-Lag Recurrent Network (TLRN); k) Recurrent Network; l) CANFIS Network (Fuzzy Logic); m) Support Vector Machine (SVM).

Once you select the architecture you can customize parameters such as the number of hidden layers, the number of processing elements and the learning algorithm. If you don't know what a parameter should be set to, you can specify that a genetic algorithm be used to optimize the setting for you.

System Requirements

Manufacturer

Manufacturer Web Site NeuroDimension, Inc.

Price Neurosolutions ,USD $195 - 2,495; NeuroSolutions and, C++ Source Code License for Workstations $3,995-4,495. See current pricing at www.neurosolutions.com/pricing.html

G6G Abstract Number 20036

G6G Manufacturer Number 101916