Results 71 to 80 of about 1,893,473 (266)

High-Level Design of Precision-Scalable DNN Accelerators Based on Sum-Together Multipliers

IEEE Access
Precison-scalable (PS) multipliers are gaining traction in Deep Neural Network accelerators, particularly for enabling mixed-precision (MP) quantization in Deep Learning at the edge.
Luca Urbinati, Mario R. Casu
doaj   +1 more source

An On‐Demand Neuromorphic Vision System Enabled by a Multi‐Paradigm Neuromorphic Device and Hierarchical Reconfigurability Designed from Device to System Level

Advanced Science, EarlyView.
An on‐demand ultra‐reconfigurable intelligent vision system with hierarchical reconfigurability from device to system levels is demonstrated. Through co‐design of a multi‐paradigm device, reconfigurable circuits, and adaptive system architecture/algorithms, the system enables seamless switching among spiking, non‐spiking, neuromorphic imaging (NI), and
Biyi Jiang, Jiayi Xu, Liang Ran, Xinhe Feng, Khalil Harrabi, Yida Li, Longyang Lin, Feichi Zhou   +7 more
wiley   +1 more source

Co‐Delivery of Sustained Release Chondroitinase ABC‐37 With Human iPSC‐Derived Neural Progenitors Promotes Transplant Survival and Functional Recovery in a Rodent Model of Stroke

Advanced Science, EarlyView.
A regenerative strategy for stroke combines human stem cell–derived neural progenitor cells with sustained release of a matrix‐modifying, thermostable chondroitinase ABC‐37 enzyme. In a rat model of stroke, co‐delivery enhanced transplanted cell survival and neuronal differentiation, degraded inhibitory extracellular matrix components, and improved ...
Nitzan Letko Khait, David Xinzheyang Li, Keyi Guo, Hong Cui, Quinton Sirianni, Dhana Abdo, Cindi M. Morshead, Molly S. Shoichet   +7 more
wiley   +1 more source

Ferroelectric Devices for In‐Memory and In‐Sensor Computing

Advanced Science, EarlyView.
Inspired by biological systems, in‐memory and in‐sensor computing overcome von Neumann bottlenecks. Ferroelectric devices can mimic synaptic functions and sense stimuli like light or force, therefore are ideal for these paradigms. This review introduces the ferroelectric devices applied for in‐memory and in‐sensor computing, covering their structures ...
Hong Fang, Ronghuan Xie, Qiang Cao, Shishen Yan, Xiaolin Wang, Limei Zheng   +5 more
wiley   +1 more source

Design of a 16-by-16-bit Unsigned Serial-parallel Multiplier using Retime Technique

Majlesi Journal of Electrical Engineering
In this paper, the structure of a 16-by-16 unsigned hybrid (serial-parallel) multiplier has been proposed. Parallel multipliers, in comparison with serial multipliers, have higher speed and higher power consumption.
Amirhossein Vafi, Ziaddin Kozehkanani, Jafar Sobhi, Mousa Yousefi   +3 more
doaj  

16 x 16 bit parallel multiplier based on 6 K gate array with 0.3 μm AlGaAs/GaAs quantum well transistors [PDF]

, 2014
The design and performance of a 16x16 bit parallel multiplier based on a 6 K gate array will be presented. This LSI semicustom IC demonstrates the high potential of the authors' AlGaAs/GaAs quantum well FETs with a gate length of 0.3 μm.
Berroth, Manfred, Hülsmann, Axel, Nowotny, Ulrich, Schneider, Joachim, Gotzeina, W., Köhler, Klaus, Raynor, Brian, Sedler, Martin, Thiede, Andreas, Hofmann, Peter, Seibel, Jörg, Kaufel, Gudrun, Hurm, Volker   +12 more
core   +1 more source

An Efficient Biological Codon Recognition Reservoir Computing System Based on Low‐Energy Epitaxial Hf0.52Zr0.48O2 Ferroelectric Memristors

Advanced Science, EarlyView.
This work reports on epitaxially grown Hf0.52Zr0.48O2 ferroelectric memristors with high stability (high durability exceeding 108 cycles and a retention time exceeding 104 s for 16 states) and ultra‐low operating energy consumption (∼121 fJ). A memristor array‐based reservoir computing system is constructed and applied for the first time in the field ...
Ying Liu, Jikang Xu, Yongqing Jia, Wenxuan Wang, Weifeng Zhang, Biao Yang, Xiaobing Yan   +6 more
wiley   +1 more source

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

Advanced Science, EarlyView.
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang, Waleed Mohammed, Dierk Raabe   +2 more
wiley   +1 more source

Neuromorphic Near‐Sensor and In‐Sensor Computing Enabled by Next‐Generation Material‐Based Sensors

Advanced Science, EarlyView.
This Review presents a structural framework that classifies neuromorphic sensing into near‐sensor and in‐sensor architectures, clarifying physical coupling between sensing and computation. The framework connects neural and synaptic device functions with recent advances in optical, mechanical, and chemical sensing, compares energy consumption and ...
Su Yeon Jung, Gwang Ya Kim, Sejin Kim, Hyunjong Seo, Se Gi Lee, Sang Min Won, Dongjoon Rhee, Joohoon Kang   +7 more
wiley   +1 more source

Photonic‐Enabled Energy‐Efficient Transparent Neuromorphic Computing Devices: A Review

Advanced Science, EarlyView.
Transparent photonic neuromorphic computing devices merge optics and brain‐inspired computing to overcome von Neumann bottlenecks with ultrafast, low‐energy processing. By exploiting transparent oxides, 2D materials, phase‐change materials, and hybrid heterostructures, these platforms enable photonic synapses, memory, and logic for see‐through edge ...
Shuvaraj Ghosh, Ki‐bum Lee, Junghyeon Lee, Seunghee Cho, Malkeshkumar Patel, Hangfei Li, Yu Wen, Ye Zhou, Joondong Kim   +8 more
wiley   +1 more source