SimpleNeuron

Simple neural network library for browser and Node.js. Work in Progress.

Installation

Via npm on Node:

npm install simpleneuron

Usage

Reference in your program:

var sn = require('simpleneuron');

Create a neuron

var neuron = sn.neuron();

It is a simple threshold neuron with trigger value = 1.

Connect a neuron with other neuron

var neuron = sn.neuron();
var input = sn.neuron();
neuron.input(input);

The input has weight 1

Connect a neuron with other neuron using a weight value

var neuron = sn.neuron();
var input = sn.neuron();
neuron.input(input, -0.5);

The input has weight -0.5.

Set the output value of neuron:

neuron.output(1);

Usually, this method is used to set the initial neuron layer values.

Get the output value of a neuron:

var result = neuron.output();

Create a network of neurons, with three layers, containing 4, 15, 3 neurons. The weights are random values between -1 and 1:

var network = ss.network([4, 15, 3]);

Get the number of neurons in a network:

var count = network.neurons();

In the previous created network, the count is 4+15+3 == 22.

Get the number of neurons in a layer:

var count0 = network.neurons(0); // 4
var count1 = network.neurons(1); // 15
var count2 = network.neurons(2); // 3

TBD

Development

git clone git://github.com/ajlopez/SimpleNeuron.git
cd SimpleNeuron
npm install
npm test

Samples

TBD

Versions

• 0.0.1 Published

License

MIT

References

• Extreme Learning Machine
• Backpropagation
• Using neural nets to recognize handwritten digits
• How the backpropagation algorithm works
• Using neural nets to recognize handwritten digits
• THE MNIST DATABASE of handwritten digits
• Neural networks in JavaScript

Books

• Neural Networks, Simon Haykin
• Fundamentals of Deep Learning, Nikhil Buduma (2017, O’Reilly)
• Anthony L. Caterini, Dong Eui Chang - Deep Neural Networks in a Mathematical Framework (2018, Springer)
• Charu C. Aggarwal - Neural Networks and Deep Learning. A Textbook (2018, Springer)
• Ian Goodfellow, Yoshua Bengio, Aaron Courville - Deep Learning (2016, The MIT Press)

Contribution

Feel free to file issues and submit pull requests — contributions are welcome<

If you submit a pull request, please be sure to add or update corresponding test cases, and ensure that npm test continues to pass.