Design of Optoelectronic In-Sensor Computing Circuit Based on Memristive Crossbar Array for In Situ Edge Extraction

The rapid development of artificial intelligence has brought a huge amount of data, and the traditional image processing architecture that separates sensing, storage and computation will face the problems of high power consumption and processing latency. Focusing on these problems, this paper proposed a design scheme of memristor-based optoelectronic sensing circuit, which can integrate image perception, storage, and processing into one entity. Without large-scale data transmission and conversion, the corresponding energy consumption can be avoided effectively. Firstly, an optoelectronic sensing circuit based on memristive crossbar array is proposed, which realizes the acquisition and in situ storage of image information by embedding the photoelectric converters into the memristive array. On this basis, the corresponding peripheral circuit is designed to accomplish the in situ edge feature extraction for the stored image. The extraction process is large-scale parallel computing in the analog domain, and the speed is significantly improved compared with the traditional solution. Moreover, the extraction accuracy of the circuit can reach more than 99%, and it also can withstand a certain degree of programming error and has strong robustness.