The MIT License (MIT)

Copyright (c) 2017 Juan Cazala - https://caza.la

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE



********************************************************************************************
                                  SYNAPTIC (v1.1.4)
********************************************************************************************

Synaptic is a javascript neural network library for node.js and the browser, its generalized
algorithm is architecture-free, so you can build and train basically any type of first order
or even second order neural network architectures.

http://en.wikipedia.org/wiki/Recurrent_neural_network#Second_Order_Recurrent_Neural_Network

The library includes a few built-in architectures like multilayer perceptrons, multilayer
long-short term memory networks (LSTM) or liquid state machines, and a trainer capable of
training any given network, and includes built-in training tasks/tests like solving an XOR,
passing a Distracted Sequence Recall test or an Embeded Reber Grammar test.

The algorithm implemented by this library has been taken from Derek D. Monner's paper:


A generalized LSTM-like training algorithm for second-order recurrent neural networks
http://www.overcomplete.net/papers/nn2012.pdf

There are references to the equations in that paper commented through the source code.