Vlsi Implementation of General Purposed Conic Section Function Neural Network
نویسندگان
چکیده
In this paper, a circuit system of General Purposed Conic Section Function Neural Network is presented. The feed-forward analog computational cells have been designed by using the current mode approach. The network is trained in a chip-in-the-loop fashion with a host computer implementing the training algorithm. The network inputs and the feed-forward signal processing are analog. The mixed analog-digital design consists of 16 inputs, 16 hidden layer neuron and 8 outputs. 8 bit precision is selected to store weight, center and angle values on the EEPROM digital memory cells. The implemented feed-forward network circuitry has been tested on a classification problem successfully.
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