Results 71 to 80 of about 3,963 (190)

A Memristor‐Based In‐Memory Computing System‐on‐Chip with Efficient Depthwise Convolution

Advanced Intelligent Systems, EarlyView.
We present a memristor‐based in‐memory computing (IMC) architecture that enables efficient depthwise convolution (DWC) acceleration. Fabricated in a system‐on‐chip with crossbar arrays, the design improves memory utilization. Experimental validation demonstrates the first hardware acceleration of DWC in IMC, achieving a digital comparable inference ...
Wenhao Song, Fuxi Cai, Sangsu Park, Zhaoyan Li, Seonghun Lee, Mingyi Rao, Woohyung Choi, Seungin Shin, Yan Zhu, Sujin Chae, Myoungsub Kim, Mingche Wu, Hyejung Choi, Yuan Dao, Jaeyun Yi, Youngman Cho, Seon Yong Cha, Ning Ge, Qiangfei Xia, Soo Gil Kim, Miao Hu, J. Joshua Yang   +21 more
wiley   +1 more source

Resource‐Aware Contrastive Scattering Meta‐Learning for Efficient Few‐Shot Acoustic Anomaly Detection

Advanced Intelligent Systems, EarlyView.
This paper introduces a resource‐aware Contrastive Scattering Meta‐Learning (CSML) framework for acoustic anomaly detection. By leveraging training‐free wavelet scattering and metric‐based meta‐learning, the model achieves competitive performance with only 50 K learnable parameters—a 98% reduction compared to state‐of‐the‐art frameworks—enabling ...
Rami Zewail, Bassem Mokhtar
wiley   +1 more source

A Two‐Stage Characterization Pipeline and Open‐Source Framework for Reproducible Tactile Sensing

Advanced Intelligent Systems, EarlyView.
The same soft tactile sensor returns different numbers when embodied in different robots. This is an Embodiment Gap that no shared framework currently captures transparently. A two‐stage characterization pipeline, paired with a FAIR open‐source digital datasheet, decouples intrinsic sensor behavior from embodiment effects and condenses cross‐laboratory
Matteo Lo Preti, Weng Buxiu, Petr Trunin, Muhammad Sunny Nazeer, Lucia Beccai, Perla Maiolino, Cecilia Laschi   +6 more
wiley   +1 more source

Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation

Advanced Intelligent Systems, EarlyView.
Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison, Kevin Nadaud, Josquin Harrison, Guillaume F. Nataf, Laura Bégon‐Lours   +4 more
wiley   +1 more source

Overcoming the Phase Discontinuity Problem in RIS Optimization: A Robust and Scalable Phase‐Aware Deep Regression Framework via Hybrid CNN–LSTM Architecture

Advanced Intelligent Systems, EarlyView.
The phase discontinuity problem—where the cyclic nature of phase angles causes catastrophic errors near the ±π boundary—is a fundamental obstacle in learning‐based reconfigurable intelligent surface (RIS) optimization. A phase‐aware hybrid CNN–LSTM framework resolves this by decomposing phase predictions into sine–cosine components, mapping circular ...
Seda Savaşçı Şen, Ali Çalhan, Murtaza Cicioğlu, Oğuzhan Demiryürek   +3 more
wiley   +1 more source

Co‐Design of Stretchable Fabric Sensors and Tiny Machine Learning for Human Interface Device‐Based Edge‐Intelligent Wearable Gloves

Advanced Intelligent Systems, EarlyView.
A flexible smart glove integrated with textile sensors enables real‐time hand gesture recognition for human–machine interaction. Using edge AI inference and Bluetooth communication, the system translates finger movements into human interface device commands to control endpoint devices efficiently.
Chi Cuong Vu, Tuan Nghia Nguyen, Minh‐Thanh Le   +2 more
wiley   +1 more source

A 2-GS/s 35.9-fJ/conv.-step Voltage-Time Hybrid Pipelined ADC with Digital Background Calibration in 28-nm CMOS. [PDF]

Micromachines (Basel)
Chang Y, Zhang C, Yang Y, Zhang C, Liu M, Chen D, Yang Y.   +6 more
europepmc   +1 more source

Energy‐Aware Perturbation Optimization for Memristor‐Array Convolutional Neural Networks

Advanced Intelligent Systems, EarlyView.
Memristor‐array inference becomes more energy efficient when layer inputs are reshaped before computation. Sinusoidal perturbation encoding with dual‐threshold screening reduces active voltage pulses and contracts ADC input‐current ranges, jointly lowering crossbar and peripheral energy while preserving accuracy across hardware MNIST validation, deep ...
Ao Xu, Lun Lu, Youpeng Wu, Yao Guo, Yi Li, Yinan Wang, Qingjiang Li   +6 more
wiley   +1 more source

L-SHADE-Optimized Active Disturbance Rejection for Sensorless PMSM Drives Under Complex Uncertainties. [PDF]

Sensors (Basel)
Chen X, Yang T, Zhang B, Zhang L.
europepmc   +1 more source

AI‐Assisted IoT‐Enabled ECG Monitoring: Integrating Foundational and Generative AI Tools for Sustainable Smart Healthcare—Recent Trends

AI &Innovation, EarlyView.
ABSTRACT The rapid evolution of the Internet of Things (IoT) has significantly advanced the field of electrocardiogram (ECG) monitoring, enabling real‐time, remote, and patient‐centric cardiac care. This paper presents a comprehensive survey of AI assisted IoT‐based ECG monitoring systems, focusing on the integration of emerging technologies such as ...
Amrita Choudhury, Kandarpa Kumar Sarma, Lachit Dutta   +2 more
wiley   +1 more source