PERFORMANCE ANALYSIS OF OPTICAL PARALLEL FULL ADDER USING ARTIFICIAL NEURAL NETWORK

Abstract

A verbal exchange today wishes for quick operational progress. This can be accomplished by replacing devices that are primarily concerned with commutation and logic with photon-based systems instead of the usual data service, the electron. The basic building blocks of superior frames are called gates. With the aid of these gates, various logical and mathematical operations can be performed. All-optical arithmetical and logical processes are eagerly expected in high-speed dialogue frameworks. In this chapter, we’ve introduced parallel models for adding two binary digits that are based on Sagnac gates with help from semiconductor optical amplifiers (SOA) and terahertz optical asymmetric demultiplexers (TOAD). We created a Full adder that works in parallel using only two TOADs as total switches. Using artificial neural networks (ANN), we have created a model of this circuit that is equivalent. Utilizing ANN, this circuit design has been validated. This optical circuit is now capable of synthesizing light as an input and successfully structuring the aspiration output in addition to speeding up calculation. This parallel circuit’s biggest advantage is that it doesn’t need synchronization for distinct inputs. An ANN model was used to analyze this circuit’s performance in detail.