Neural network technology for pattern recognition, stock prediction and market forecasting


Pattern recognition

DCT-ANN Face Identification

Wavelet-ANN Face Recognition

Text-Independent Speaker Recognition based on ANN

Assembler-based Neural Network Simulator

Facial Expression Recognition System

Iris Recognition Based on Neural Networks

Neural Networks Based Signature Recognition

Eye Detection Based Facial Expression Recognition

Gait Recognition System

Leaf Recognition System

Optical Character Recognition

Neural Network Fingerprint Recognition

Keystroke Recognition

EEG Recognition

Neural Network Speech Recognition

Image processing

Image Compression With Neural Networks

Stock Market Forecasting

Neural Network Forecasting

External resources

Advanced Source Code .Com

Genetic Algorithms .It

Face Recognition .It

Iris Recognition .It

Matlab MEX Interface to Assembler-based Neural Network Training and Simulation

Download now Matlab source code
Requirements: Matlab.

ANNS is a neural network simulator based on assembler language with a simple and intuitive Matlab interface. ANNS package dynamically generates ASM code, automatically embedding it into Matlab MEX file (Matlab C interface) for a fast and highly optimized code for neural network training and simulation. ANNS package is particularly suitable for pattern recognition tasks, when speed becomes the most relevant issue. ANNS package implements the backpropagation algorithm and includes:
  • arbitrary length of input feature vectors
  • one hidden layer (arbitrary number of hidden neurons)
  • hyperbolic tangent activation function on the hidden layer
  • linear activation function on the output layer
  • scalar output
ANNS package uses the Netwide Assembler.
The Netwide Assembler is available at

Index Terms: Matlab, assembler, Mex, c, interface, neural network, asm, Netwide Assembler, ann, artificial neural networks, nn.

Release 1.0 Date 2007.01.18
Major features:

Neural Networks . It Luigi Rosa mobile +39 3207214179