cVision Licensing

On request we will send you a customer licence information file containing all necessary information to activate cVision on your computer. Customers holding a valid licence are entitled to download the latest cVision updates for free.

At present we are distributing the following three product levels, the particular levels are to be activated by a licence key.

• Standard Level
• Professional Level
• Enterprise Level

All levels include all features to create and train a single neural network successfully, the features hold in detail

• Numerical and Categorical Data Handling
• Heuristic Network Initialization
• Intelligent Input Neurons
• Local Adaptive Learning Rules
• Cluster Learning
• Superior Stopping Criteria
• Automatic Network QC

The table below summarizes the differences between the particular cVision product levels.

The Multi Linear Regression (MLR) is a special and easy case of a neural network. The MLR has only input and output layer without any hidden neurons in between. The figure below sketches the network like structure of an MLR expert.

MLR

The Multi Layer Perceptron (MLP) is organized in layers, each layer containing an arbitrarily number of hidden neurons. Multi Layer Perceptrons have an input layer, one ore more hidden layers and an output layer. The Improved Multi Layer Perceptron (iMLP) has additional input output shortcut connections, drawn in orange in the right picture below.

MLP		iMLP

The Generalized Multi Layer Perceptron (GMP) is organized in layers, each layer containing an arbitrarily number of hidden neurons. Generalized Multi Layer Perceptrons have an input layer, one ore more hidden layers and an output layer. The Improved Generalized Multi Layer Perceptron (iGMP) has additional input output shortcut connections, drawn in orange in the right picture below.

GMP		iGMP

The Completely Connected Perceptron (CCP) has in opposite to the Multi Layer Perceptron the advantage, that a network growing process is straight forward since it is no longer necessary to find an optimal choice for the number of hidden layers. Completely Connected Perceptrons have an input layer, one single input block consisting of an arbitrary number of hidden neurons and they have of course an output layer. The Improved Completely Connected Perceptron (iCCP) has additional input output shortcut connections, drawn in orange in the right picture below.

CCP		iCCP