What is "neural-networks"

Artificial neural networks (Rnas) are computer models inspired by the central nervous system of an animal (in particular the brain) that is able to perform machine learning as well as pattern recognition. Artificial neural networks are usually presented as systems of "interconnected neurons that can compute input values". The most important property of neural networks is the ability to learn from their environment and thereby improve their performance. This is done through an iterative process of adjustments applied to your weights, training. Learning occurs when the neural network reaches a generalized solution to a class of problems. It is called a learning algorithm to a set of well-defined rules for solving a learning problem. Another important factor is the way in which a neural network relates to the environment.

Applications:

• Automatic Recognition of Targets
• Character Recognition
• Robotics
• Diagnosis Médico
• Sensoriamento Remoto
• Voice Processing
• Biometrics