Novel Ternary Adder and Multiplier Designs Without Using Decoders or Encoders

Project Code :TVPGBE124

Objective

In this project, the 32 nm CNTFET-based Ternary Half Adder (THA) and Multiplier (TMUL) circuits use novel ternary unary operator circuits and implement two power supplies Vdd and Vdd/2 without using any ternary decoders, basic logic gates, or encoders to minimize the number of used transistors and improve the energy efficiency.

Abstract

In this project, the 32 nm CNTFET-based Ternary Half Adder (THA) and Multiplier (TMUL) circuits use novel ternary unary operator circuits and implement two power supplies Vdd and Vdd/2 without using any ternary decoders, basic logic gates, or encoders to minimize the number of used transistors and improve the energy efficiency. Multiple-Valued Logic systems present significant improvements in terms of energy consumption over binary logic systems. This paper proposes new ternary combinational digital circuits that reduce energy consumption in low-power nano-scale embedded systems and Internet of Thing (IoT) devices to save their battery consumption. 

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

Software Requirements:

  • H-spice
  • Technology files: 32nm

Hardware Requirements:

  • Microsoft® Windows XP
  • Intel® Pentium® 4 processor or Pentium 4 equivalent with SSE support 
  • 512 MB RAM 
  • 100 MB of available disk space


Learning Outcomes

In this project, the 32 nm CNTFET-based Ternary Half Adder (THA) and Multiplier (TMUL) circuits use novel ternary unary operator circuits and implement two power supplies Vdd and Vdd/2 without using any ternary decoders, basic logic gates, or encoders to minimize the number of used transistors and improve the energy efficiency. Multiple-Valued Logic systems present significant improvements in terms of energy consumption over binary logic systems. This paper proposes new ternary combinational digital circuits that reduce energy consumption in low-power nano-scale embedded systems and Internet of Thing (IoT) devices to save their battery consumption. 

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