Neural Network for external devices control (finger print entry)

摘要

Neural networks are composed of simple elements operating in parallel. These elements are inspired by biological nervous systems. As in nature, the network function is determined largely by the connections between elements. We can train a neural network to perform a particular function by adjusting the values of the connections (weights) between elements. Commonly neural networks are adjusted, or trained, so that a particular input leads to a specific target output. The network is adjusted, based on a comparison of the output and the target, until the network output matches the target. Typically many such input/target pairs are used to train a network. This paper takes the finger print as an input to the neural network. Once the finger print is recognized by the neural network, the output will be used to activate an external device giving access permission, welcome words and issuing a paper. In case of denial of the finger print by the neural network an alarm occurs and a denial message get displayed. A Matlab package is used for accomplishing the neural network algorithm plus an interface circuit is designed to drive the external devices.