Design and Implementation of In - Exact Wallacetree Multiplier Through Reversible-Logic
Keywords:
Wallace Tree Multiplier, and Ancilla Input (AI), Convolution Neural Networks (CNN), Structural Similarity Index Measure (SSIM), Ladner-Fischer adder.Abstract
In this study, an inexact Baugh-Wooley Wallace tree multiplier with a unique architecture for an inexact 4:2 compressor is proposed. It is optimized for realization through the use of different logics that are reversible logic. Gate- Count, Quantum - Cost , Garbage – Output , and Ancilla-Input scales are used to quantify the effectiveness of the proposed reversible logic-based realization of the proposed and Baugh-Wooley Wallace tree multiplier. In this work, an 8 × 8 Baugh-Wooley-Wallace-tree-multiplier and inexact 4:2 compressor is used to design this implementation. The suggested multiplier has the lowest accuracy metrics (MED and MRED) of any known compressor-based multiplier design. There are two applications for the suggested multiplier. 1) Image processing: rationalized db6 wavelet filters bank one-level decomposition and picture smoothing; 2) convolution neural networks (CNN).The Structural Similarity Index Measure (SSIM) is used to gauge how effective the suggested multiplier is in image processing applications.
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