https://github.com/nlgranger/nnbox
A neural network toolbox for matlab
https://github.com/nlgranger/nnbox
cnn matconvnet matlab neural-network toolboxes
Last synced: 1 day ago
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A neural network toolbox for matlab
- Host: GitHub
- URL: https://github.com/nlgranger/nnbox
- Owner: nlgranger
- License: mit
- Created: 2016-07-14T17:22:02.000Z (about 9 years ago)
- Default Branch: master
- Last Pushed: 2016-07-14T17:22:38.000Z (about 9 years ago)
- Last Synced: 2023-10-20T22:05:52.721Z (almost 2 years ago)
- Topics: cnn, matconvnet, matlab, neural-network, toolboxes
- Language: Matlab
- Size: 90.8 KB
- Stars: 19
- Watchers: 6
- Forks: 4
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: COPYING
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README
# NNBox
NNBox is a Matlab © toolbox for neural networks. Many other toolboxes are
already available for matlab and may either offer more models, a higher levels
of support, better optimization, or simply a bigger user community... This
toolbox tries to focus on different objectives:
- Providing very clear and simple implementations of some neural networks
models and architectures.
- Providing a simple template to implement new models rapidly
- Providing a flexible interface where building blocks can be arranged
together easily.
In particular, this library provides support for Restricted Boltzmann Machines
(RBM), Convolutional Neural Networks (CNN), simple perceptrons models. It
allows to arrange these models in parallel, as stacked multiple layers, or even
in a Siamese network architecture.
This library does not focus on completeness though, because attempting to do so
rarely gives satisfying results. Instead it tries to provide simple and
flexible architectural fundations to help you implement your own model quickly.
For your information, here is a list of other existing libraries:
- [Matlab Neural Network toolbox](http://fr.mathworks.com/help/nnet/index.html)
- [DeepLearnToolbox](https://github.com/rasmusbergpalm/DeepLearnToolbox)
A popular deep learning toolbox
- [MEDAL](https://github.com/dustinstansbury/medal) Similarily provides
implementations for several sorts of Deep Learning models.
- [MatConvNet](http://www.vlfeat.org/matconvnet/) Provides awrapper to a C++
implementation of convolutional neural networks. It is actually used here
for the CNN model.
## Requirements
As far as I can tell, any version of matlab above R2011a should work, R2014a
is known to work. Octave is not supported because classes are not yet fully
supported.
## Installation
Just add nnbox subfolders to your path:
```matlab
addpath('nnbox/utils:nnbox/networks:nnbox/costfun:nnbox/distances');
```
CNN implementation requires the [MatConvNet](http://www.vlfeat.org/matconvnet/)
library as a backend, follow installation instructions and add the matlab
bindings to the path.
## Examples
```matlab
X = [0 1 0 1;
0 0 1 1];
Y = [0 .5 .5 1];
net = Perceptron(2, 1, struct('lRate', 0.5));
trainOpts = struct('nIter', 100, 'displayEvery', 10);
train(net, SquareCost(), X, Y, trainOpts);
```
- MNIST figure recognition using a Deep belief network :
[examples/MNIST_DNN.m](examples/MNIST_DNN.m)
## Documentation
Refer to [DOCUMENTATION.md](DOCUMENTATION.md)