Neurons networked in the brain are what process many pieces of information and help the brain reach a solution to a particular problem. In this project, we have developed a neural network approach to analog to digital conversion. Our network architecture utilizes feedback from the outputs of each neuron as inputs to all the other neurons. Based on the information contained in the feedback, the network will converge so that an optimum solution will be reached. In other words, all of the neurons know what each of the other neurons are doing. Therefore the digital output will converge to a decision which comes close to the analog input. Due to the feedback, there will be several advantages of the neural network A/D converter over a conventional A/D converter including speed, resolution and stability.
 

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