The challenging deployment of compute-intensive applications from domains such as
Artificial Intelligence (AI) and Digital Signal Processing (DSP), forces the community of …

Multiplication is one of the essential functions in all digital systems. The evaluation of digital
system, have brought out new challenges in VLSI (Very Large Scale Integration) designing …

The focus of existing designs on approximate radix-8 Booth multipliers has been on ASIC-
based platforms. These multipliers are based on an approximation as defined for ASIC …

In this paper, we present a novel approximate computing scheme suitable for realizing the
energy-efficient multiply-accumulate (MAC) processing. In contrast to the prior works that …

Approximate recursive multipliers exhibit low-power operation because they are designed
using smaller power-efficient approximate multiplier blocks. These building blocks can be …

We present an approximate logarithmic multiplier with two-stage operand trimming, which
prioritises area and energy consumption while retains acceptable accuracy. The multiplier …

This paper proposes an energy-efficient approximate multiplier which combines radix-4
Booth encoding and logarithmic product approximation. Additionally, a datapath pruning …

The rapid growth of demanding applications in domains applying multimedia processing
and machine learning has marked a new era for edge and cloud computing. These …

Low-power keywords recognition has been a focus of acoustic signal processing for several
decades. This work investigates the domain-specific speech recognition microprocessor …

Artificial intelligence on edge is a growing research field. In this brief, we propose a novel re-
encoding scheme for reducing the size of the weights of deep neural networks (DNNs). The …