New Model based on ANN for Implementing Real Time ۴bit Binary to Gray Decoder

Nowadays, various codes are used to enhance the security of computer networks, to make it easier to work with binary codes for ordinary people, and also to facilitate the detection and correction of errors in sending and receiving information. One of the most important codes used in shaft encoder sensors is Gray code. This code is used to determine the exact angle of rotational motion. Previously, these sensors used binary code. During using these codes in encoder shafts, several important faults occurred. For solving these problems, scientists suggested that using Gray code would be efficient. Various techniques are available to convert binary code to Gray code. In this paper, an approach based on Artificial Neural Networks (ANN) is used to convert binary code to Gray. Backpropagation Algorithm for feedforward ANN has been simulated using MATLAB for converting these codes. The designed ANN is trained for all possible combinations of codes.

کلیدواژه ها:

Artificial Neural Network ، Gray code ، Binary code ، Real-time ، Decoder