Abstract: Machine Learning (ML) has been one of the applications of approximate circuits. These circuits, part of approximate computing, can be implemented ...

A 4:2 compressors with inexact logic minimization by flipping some of the output bits considering efficiency/accuracy into account is presented, ...

This research work employs probabilistic logic minimiza- tion on exact 4:2 compressor, where bit flipping in the minterms of Boolean functions of SUM, Carry and ...

Machine Learning (ML) has been one of the applications of approximate circuits. These circuits, part of approximate computing, can be implemented using ...

In [12] , the authors have proposed an approximate compressor using inexact logic minimization and embedded it in the multiplier for power efficiency and ...

This paper presents an energy-efficient approximate multiplier with a novel imprecise 4-2 compressor based on incomplete-sorted circuits. The proposed ...

Machine Learning Based Power Efficient Approximate 4:2 Compressors for Imprecise Multipliers. (2019). Not Available. Content Type: proceedings-article.

In this paper, we propose four approximate 4:2 compressors. We utilize the gate diffusion input to achieve significant area reduction in the proposed ...

This brief introduces two unsigned approximate multiplier designs: MUL1, tailored for high-precision applications, and MUL2, optimized for low-power usage.

In this paper, two approximate multipliers based on an approximate 4:2 compressor and two 4-bit full adders with minimizing computational costs are proposed.