Results 181 to 190 of about 6,225,654 (298)

Efficient In‐Hardware Matrix–Vector Multiplication and Addition Exploiting Bilinearity of Schottky Barrier Transistors Processed on Industrial FDSOI

Advanced Electronic Materials, EarlyView.
ABSTRACT Machine learning and Artificial Intelligence (AI) tasks have stretched traditional hardware to its limits. In‐hardware computation is a novel approach that aims to run complex operations, such as matrix–vector multiplication, directly at the device level for increased efficiency.
Juan P. Martinez, Niladri Bhattacharjee, Yuxuan He, Giulio Galderisi, Brojogopal Sapui, Sara Mannaa, Ian O'Connor, Violetta Sessi, Peter Javorka, Thomas Mikolajick, Jens Trommer   +10 more
wiley   +1 more source

Climate change exacerbates disparities of energy resilience in New York City. [PDF]

Nat Commun
Xu L, Lin N, Perera ATD, Spaulding AC, Wang Z, Oppenheimer M, Blackshaw CY, Poor HV.   +7 more
europepmc   +1 more source

On the Role of Preprocessing and Memristor Dynamics in Reservoir Computing for Image Classification

Advanced Electronic Materials, EarlyView.
ABSTRACT Reservoir computing (RC) is an emerging recurrent neural network architecture that has attracted growing attention for its low training cost and modest hardware requirements. Memristor‐based circuits are particularly promising for RC, as their intrinsic dynamics can reduce network size and parameter overhead in tasks such as time‐series ...
Rishona Daniels, Duna Wattad, Ronny Ronen, David Saad, Shahar Kvatinsky   +4 more
wiley   +1 more source

A CPU-NPU Heterogeneous Edge Fault Diagnosis Framework for Industrial Sensor Data. [PDF]

Sensors (Basel)
Xu K, Wang H, Li C, Liu H, Xing C.
europepmc   +1 more source

Experimental Demonstration of Temporally Aware Fault‐Tolerant Sensor Fusion Using Memristive Associative Learning

Advanced Electronic Materials, EarlyView.
In dynamic driving scenarios, the proposed approach ensures only temporally aligned sensor inputs to make driving decisions, preventing false activations. By enabling selective hardware‐level learning, it achieves fast, reliable responses under noisy conditions.
Kapil Bhardwaj, Ashfak Nehal, Dmitrii Semenov, Roman Sotner, Sayani Majumdar   +4 more
wiley   +1 more source

Scenario-based occupational risk assessment for power grid maintenance workers. [PDF]

PLoS One
Wang W, Zhao X, Wang L, Qin T.
europepmc   +1 more source

Array‐Level Characterization of Cryogenic RRAM

Advanced Electronic Materials, EarlyView.
This paper reports the first array‐level comprehensive electrical characterization of a 1024‐device HfO2‐based RRAM array from 300, 77 to 4 K, covering forming, set/reset switching, endurance, retention, relaxation, and read disturb. The results manifest the high performance of RRAM array at cryogenic temperatures and huge application potential for ...
Yuyao Lu, Ruofei Hu, Zhixing Jiang, Feng Xu, Bin Gao, Jianshi Tang, He Qian, Huaqiang Wu   +7 more
wiley   +1 more source

Mitigation of inductive coupling effects on buried pipelines using gradient control conductors of overhead line configuration and hippopotamus optimization algorithm. [PDF]

Sci Rep
Hachani K, Bachir B, Rabah D, Bessedik SA, El-Sehiemy RA.   +4 more
europepmc   +1 more source

Stochastic‐MTJ Sampler Arrays for In‐Array Monte–Carlo Estimation

Advanced Electronic Materials, EarlyView.
A low‐energy‐barrier magnetic tunnel junction array is operated as a probability‐domain sampler: each cell's random switching, programmed through a shared digital‐to‐analog converter, makes the per‐column multiply–accumulate an unbiased Monte–Carlo expectation estimator that returns both a mean and a calibrated uncertainty.
Ran Zhang, Nellie Laleni, Sina Ranjbar, Andreas Tsiougkos, Nandakishor Yadav, Vasilis Pavlidis, Thomas Kämpfe   +6 more
wiley   +1 more source

A Unified Flash Memory Platform for Mode-Adaptive and Robust AI Computation. [PDF]

Adv Sci (Weinh)
Yu D, Hwang H, Oh B, Lee J, Yu S, Kim TH, Kim H.   +6 more
europepmc   +1 more source