SNARLI (Simple Neural ARchitecture LIbrary) is a Java package containing the folloing classes: BPLayer also supports sigma-pi connections and back-prop-through-time, allowing you to build just about any kind of back-prop network found in the literature.

SNARLI differs from existing neural-net packages in two important ways: First, it is not GUI-based. Instead, it is meant as a code resource that can be linked directly to new or existing Java-based projects, for those who want to try a neural-network approach without having to write a lot of new code. Given the variety of platforms that currently interface to Java, from HTML to Matlab, it made more sense to me to focus on the neural net algorithms, and leave the GUI development to others.

Second, SNARLI gets a great deal of mileage out of a single class (BPLayer), instead of adding a new class for each type of network. Using this class, my students and I have been able to construct a large variety of back-prop networks, from simple perceptrons through Pollack's
RAAM, with very little additional coding. We have used these networks successfully in coursework , thesis projects, and research.

Future versions of SNARLI may include classes to support other popular architectures, such as Support Vector Machines (SVMs), Hopfield Nets, and Long Short-Term Memory (LSTM), as user interest dictates.