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Neural Networks

Also referred to a parallel distributed processing, neural networks are in the realm of advanced artificial intelligence and robotics, and are often used in pattern recognition... in other words, to find order out of apparent chaos. Typical examples of applications using neural networks include face recognition, voice recognition, character and handwriting recognition.

Neural networks attempt to analyze data in the same way that the human brain is believed to work. For example, walk into any room, even a room that you have never been to before. You can instantly differentiate between a television and a computer monitor, or a coffee cup and a photograph of a coffee cup. Before the advent of neural networks, a computer could take hours to determine what was in the room.

Neural networks are on the forefront of national security, where a computer can scan faces in a crowd and select individuals who match the facial profiles of known terrorists and criminals.

Neural networks are particularly effective for predicting events when the networks have a large database of prior examples to draw on.

Lotto Sorcerer uses a type of back-propagating neural network to recognize patterns in winning numbers that have been chosen in the past. By finding the most successful pattern, a strategy is chosen to select numbers for subsequent drawings. If a pattern exists, Lotto Sorcerer will find it.

If you want to investigate the fascinating science of neural networks in greater depth, a wide variety of resource and reference material is available on the Internet. Here are some good links (in alphabetical order):