ARTIFICIAL NEURAL NETWORKS TECHNOLOGY

ARTIFICIAL NEURAL NETWORKS TECHNOLOGY

Abstract:

Artificial neural networks are one of the promises for the future in computing. They offer an ability to perform tasks outside the scope of traditional processors. They can recognize patterns within vast data sets and then generalize those patterns into recommended courses of action.

“Neural networks learn, they are not programmed”

Yet, even though they are not traditionally programmed, the designing of neural networks does require a skill. It requires an "art." This art involves the understanding of the various network topologies, current hardware, current software tools, the application to be solved, and a strategy to acquire the necessary data to train the network. This particular paper gives a brief idea about the ARTIFICIAL NEURAL NETWORKS, their working, new advents and future developments.

What are Artificial Neural Networks?:

Artificial Neural Networks are relatively crude electronic models based on the neural structure of the brain. The brain basically learns from experience. It is natural proof that some problems that are beyond the scope of current computers are indeed solvable by small energy efficient packages. This brain modeling also promises a less technical way to develop machine solutions. This new approach to computing also provides a more graceful degradation during system overload than its more traditional counterparts.


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