Results 121 to 130 of about 7,113 (299)

Design of floating point multiplier using approximate hybrid Radix-4/ Radix-8 booth encoder for image analysis

e-Prime: Advances in Electrical Engineering, Electronics and Energy
This paper presents a novel power efficient Hybrid floating point multiplier (HFPM) with approximate hybrid radix-4/radix-8 booth encoder. This approach efficiently increases the speed of operation and optimises hardware.
Pranose J. Edavoor, Aswini K. Samantaray, Amol D. Rahulkar   +2 more
doaj   +1 more source

Experimental Characterization and Constitutive Modeling of the Effect of Prior Inelastic Strain on the Viscoplastic Behavior of AD730 at 700 °C

Advanced Engineering Materials, EarlyView.
This study shows that superalloys used in aircraft engine disks become much more prone to deformation at high temperatures if they have been strained during manufacturing. This effect increases with the level of prior strain but eventually reaches a limit.
Fabio Machado Alves da Fonseca, Patrick Villechaise, Malik Durand, Arnaud Longuet, Florent Coudon, Loïc Signor, Julien De Jaeger, Dominique Eyidi, Nathalie Bozzolo, Jonathan Cormier   +9 more
wiley   +1 more source

A Dislocation Perspective on Strength and Toughness in Ceramics

Advanced Engineering Materials, EarlyView.
Dislocations in ceramics enjoy a long but yet under‐appreciated history. The three research waves for dislocations in ceramics highlight the topic evolution over the last 90 years. This review focuses on the impact of dislocation on strength and toughness in ceramics.
Xufei Fang
wiley   +1 more source

Image Processing using Approximate Data-path Units [PDF]

, 2013
: In this work, we present approximate adders and multipliers to reduce data-path complexity of specialized hardware for various image processing systems.

core  

AMG: Automated Efficient Approximate Multiplier Generator for FPGAs via Bayesian Optimization

, 2023
Approximate computing is a promising approach to reduce the power, delay, and area in hardware design for many error-resilient applications such as machine learning (ML) and digital signal processing (DSP) systems, in which multipliers usually are key ...
Zhou, Hao, Li, Zhen, Wang, Lingli
core  

Compatibility of Methacrylate Based Resins Controls Interfacial Failure and Toughness in 3D‐Printed Multimaterial Composites

Advanced Engineering Materials, EarlyView.
This work shows that the mechanical performance of multimaterial digital light processing (DLP) printed thermoset composites is governed by resin compatibility and interfacial design rather than spatial patterning alone. Brittle and ductile resin combinations produced premature interfacial failure, while graded interfaces and mechanically compatible ...
Ahmed M. H. Ibrahim, Li Meng, Ahmad R. Najafi, Nicolas J. Alvarez   +3 more
wiley   +1 more source

Advanced Electron Microscopy and Microcomputed Tomography Analysis of Single‐Crystal Ni‐Base Superalloys After Short‐Term Multiaxial Creep

Advanced Engineering Materials, EarlyView.
This work studies the anisotropic behavior of circular notched tensile specimens of Ni‐base superalloy single crystals during high‐temperature tensile creep along [001], [110], and [111]. Correlative scale‐bridging imaging of specimens reveals early rupture along [110] because 1) plastic deformation proceeds faster at notch center; 2) more (brittle ...
Leonardo Agudo Jácome, Lijie Cao, Christoph Somsen, Johannes Boes, René Hesse, Werner Theisen, Gunther Eggeler   +6 more
wiley   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

Energy-Efficient Neural Network Acceleration Using Most Significant Bit-Guided Approximate Multiplier

The escalating computational demands of deep learning and large-scale models have led to a significant increase in energy consumption, highlighting the urgent need for more energy-efficient hardware designs.
Pengfei Huang, Chenghua Wang, Ke Chen, Bin Gong   +3 more
core   +1 more source

Design of Approximate Compressors for Multiplication

, 2017
Approximate computing is a promising technique for energy-efficient Very Large Scale Integration (VLSI) system design. It is best suited for error-resilient applications such as signal processing and multimedia. Approximate computing reduces accuracy but
Deepa P, Anusha Gorantla
core   +1 more source