All connections are converted to time-delays when the network runs, but this is completely hidden from the user. There are no fancy graphical tools to monitor network behavior or characteristics . The communication with external data is handled conveniently by stream objects in the network. A network may have multiple input and output streams. The streams perform the normalization of the data to values in the range suitable for ANN computation.
Streams can read data in several different file formats.
The only training algorithm available is a fast implementation of the back-propagation learning algorithm. For this type of problems, back-propagation with momentum is a good choice. Units of several different types can be arbitrarily mixed in a network. Many different error functions are supported and can be arbitrarily mixed in a network. No graphics support for viewing the networks.