Ultra-Efficient Low-Power Retinal Nano Electronic Circuit for Edge Enhancement and Detection Using 7 nm FinFET Technology

Abstract

This study proposed a 7 nm FinFET based analog one pixel circuit block inspired by lateral inhibition phenomenon to perform edge enhancing and edge detection of optoelectronic image. This plays a crucial role in retinomorphic applications like artificial human retinal functions. Proposed Edge enhancement and edge detection circuits are constructed using two distinct 750×750-pixel silicon networks. First the single pixel circuit cell is reconstructed with the lateral inhibition phenomenon, then the circuit using GPDK (Generic Process Design Kit) in 180 nm, 90 nm, and 45 nm CMOS technology is designed. We used 3×3 convolution process for image masking in digital and analog image signal processing which gives more accuracy in term of object recognition. The power consumption in each case is obtained to be approximately 19.71 μW, 4.18 μW and 1.62 μW for edge enhancing and 23.76 μW, 7.99 μW and 3.41 μW for edge detection which is much larger than the power consumed by the same circuit is implemented with 7 nm FinFET (Fin Field Effect Transistor) technology, 21.91 pW and 24.85 pW. In addition, the size reduction of the circuit reduced by 84% compared with 45 nm CMOS, increases the accuracy of the circuit by 30%. Results confirm that FinFET based single pixel circuit consumes less power, reduces size, and gives higher accuracy. The output from all the circuits has been matched with the biological response.