Programmable quantum-dots memristor based architecture for image processing

An analog Cellular Neural Network (CNN) architecture employing quantum dots to realize various real time image processing applications such as edge and line detections and motion estimation is proposed. In order to obtain programmability to switch between applications, memristive connections between neighboring cells, and for signal amplification and locking resonant tunneling diodes (RTDs) are utilized. Simulations are carried out on a 2D array of the proposed cell structure to demonstrate edge detection and line detection tasks. This work also provides analytical models and simulation results to prove above mentioned real time image processing functionalities.