Artificial Retina Using A Hybrid Neural Network With Spatial Transform Capability
This work addresses hardware implementation challenges for artificial retinas, though it appears incremental in combining existing analog and digital components.
The paper presents a hybrid digital/analog neural network designed as an artificial retina capable of performing spatial discrete cosine transforms, with results demonstrated through Matlab and Spice simulations and a practical device implementation.
This paper covers the design and programming of a hybrid (digital/analog) neural network to function as an artificial retina with the ability to perform a spatial discrete cosine transform. We describe the structure of the circuit, which uses an analog cell that is interlinked using a programmable digital array. The paper is broken into three main parts. First, we present the results of a Matlab simulation. Then we show the circuit simulation in Spice. This is followed by a demonstration of the practical device. This system has intentionally separated components with the specialty analog circuits being separated from the readily available digital field programmable gate array (FPGA) components. Further development includes the use of rapid manufacture-able organic electronics used for the analog components. The planned uses for this platform include crowd development of software that uses the underlying pulse based processing. The development package will include simulators in the form of Matlab and Spice type software platforms.