Redes neurais para reconhecimento de padroes ( ingles )

The neural approach to pattern recognition

http://ubiquity.acm.org/article.cfm?searchterm=pattern...

Articles
THE NEURAL APPROACH TO PATTERN RECOGNITION
April 2004 | BY JOHN PETER JESAN

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Artificial neural networks could surpass the capabilities of conventional computer-based pattern recognition systems. The word "recognition" plays an important role in our lives. It is a basic property of all human beings; when a person sees an object, he or she first gathers all information about the object and compares its properties and behaviors with the existing knowledge stored in the mind. If we find a proper match, we recognize it. For example, when we see a dog, first we recognize that it's an animal; when we take closer look, we recognize that it has four legs and a tail. As we are aware, most animals have four legs and a tail. The question is how we recognize that it's a dog. We look at other properties of dogs such as face, shape of ear, mouth, nose, body structure, teeth, eyes and voice. We might have seen lots of dogs and learned what a dog will look like. After making proper analysis of all the properties, we recognize and conclude that it is a dog. Going a step further, we can differentiate or recognize our own dog when our dog is with other dogs. This recognition concept is simple and familiar to everybody in the real world environment, but in the world of artificial intelligence, recognizing such objects is an amazing feat. The functionality of the human brain is amazing; it is not comparable with any artificial machines or software. Let us go deeper and analyze what is recognition and how it is done through machines. Pattern Recognition The act of recognition can be divided into two broad categories: recognizing concrete items and recognizing abstract items. The recognition of concrete items involves the recognition of spatial and temporal items. Examples of spatial items are