Programmable Photoelectric Memristor Gates for In Situ Image Compression. (14th July 2020) - Berco, Dan; Ang, Diing Shenp; Kalaga, Pranav Sairam
Abstract : Integrated circuits designed to perform mathematical operations, such as Fourier transforms and matrix multiplications, in artificial visual perception and intelligent image processing are mainly constructed of conventional logic gates. However, Boolean logic is probably not the most optimal approach for brain‐inspired computing due to the fuzzy nature of biologic neural networks. This work demonstrates an application based on programmable fuzzy‐logic gates capable of combined photoelectric computations. Such an apparatus may be used to perform image compression immediately upon acquisition without having the need to rely on interaction between separate processor and sensor modules. It is based on resistive memory devices capable of state transitions in response to both electronic and light stimulations. Material nonimplication and logical true operations are first presented. A more complex functionality for material nonimplication of a logic conjunction is then demonstrated. These gates are then used as building blocks in the design and simulation of a configurable matrix multiplication unit that effectively implements in situ image compression. A membership function (FUZZIFY) that may be used to map strict logic levels to incremental fuzzy analog ones is also shown. Finally, an approach for integrating conventional logic with a fuzzy computation is discussed. Abstract : The authors demonstrate the design principles for an in situ image compression circuit, based on programmable photoelectric memristor gates. When configured as a crossbar array, it may be used to reduce the size of a directly imprinted image as well as to perform fuzzy‐logic computations immediately upon acquisition, thus bypassing the need to communicate information to a processing unit.