Results 71 to 80 of about 763 (210)

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

Ion‐Gating Reservoir Computing for Preprocessing‐Free Speech Recognition from Throat Vibrations

Advanced Electronic Materials, EarlyView.
This work presents a throat‐mounted mechanoelectric sensor integrated with an ion‐gel/graphene reservoir device for on‐device speech recognition. The system converts raw biomechanical vibrations into rich nonlinear current dynamics, enabling efficient classification through a simple linear readout. The approach highlights a compact and tunable physical‐
Daiki Nishioka, Akito Tateyama, Hina Kitano, Takashi Nakanishi, Kazuya Terabe, Takashi Tsuchiya   +5 more
wiley   +1 more source

Deep Photonic Reservoir Computer for Speech Recognition

IEEE Transactions on Neural Networks and Learning Systems
Speech recognition is a critical task in the field of artificial intelligence and has witnessed remarkable advancements thanks to large and complex neural networks, whose training process typically requires massive amounts of labeled data and computationally intensive operations.
Enrico Picco, Alessandro Lupo, Serge Massar   +2 more
openaire   +4 more sources

PAM-4 Transmission at 1550 nm Using Photonic Reservoir Computing Post-Processing

IEEE Access, 2019
The efficacy of data decoding in contemporary ultrafast fiber transmission systems is greatly determined by the capabilities of the signal processing tools that are used. The received signal must not exceed a certain level of complexity, beyond which the
Apostolos Argyris, Julian Bueno, Ingo Fischer   +2 more
doaj   +1 more source

Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization

Advanced Electronic Materials, EarlyView.
Artificial intelligence accelerates the discovery and optimization of HfO2‐based fluorite ferroelectrics by linking synthesis, structure, properties, and device performance. Machine learning, deep‐learning analysis, and AI‐driven atomistic modeling enable predictive design, dopant screening, and closed‐loop optimization toward next‐generation ...
Faizan Ali, David Lehninger, Florencio Sánchez, Ignasi Fina   +3 more
wiley   +1 more source

Photon number-resolving quantum reservoir computing

Optica Quantum
Neuromorphic processors improve the efficiency of machine learning algorithms through the implementation of physical artificial neurons to perform computations. However, while efficient classical neuromorphic processors have been demonstrated in various forms, practical quantum neuromorphic platforms are still in the early stages of development.
Sam Nerenberg, Oliver D. Neill, Giulia Marcucci, Daniele Faccio   +3 more
openaire   +2 more sources

Metal nanostructure‐coupled label‐free localized surface plasmon resonance biosensors for rapid and sensitive disease diagnosis

BMEMat, EarlyView.
LSPR biosensing enables rapid, sensitive, and low‐sample‐volume detection of biomarkers, with broad applications in diagnosing cancer, infectious, and chronic diseases. Advances in nanostructure design, micro/nanofabrication, and microfluidic integration have expanded the potential of LSPR sensors in biomedical diagnostics.
Zhaoxin Geng, Yunfei Sha, Jiongyan Yang, Hongru Yang, Xiao Liang   +4 more
wiley   +1 more source

Graphene Materials for Sustainable Energy Applications: A Contemporary Perspective

Carbon Energy, EarlyView.
ABSTRACT Graphene has garnered significant attention as a promising material with great potential for contributing to sustainable energy initiatives, such as RE100 (100% renewable energy initiative) and CF100 (100% carbon‐free initiative). This review aims to explore the potential of graphene for advancing renewable energy applications by highlighting
Niraj Kumar, Seul‐Yi Lee, Roop L. Mahajan, Soo‐Jin Park   +3 more
wiley   +1 more source

Optimising complexity and learning for photonic reservoir computing with gain-controlled multimode fibres

Frontiers in Nanotechnology
Nonlinear photonics is a promising platform for neuromorphic hardware, offering high-speed processing, broad bandwidth, and scalable integration. Within this framework, Reservoir Computing (RC) and Extreme Learning Machines (ELM) are powerful approaches ...
Giulia Marcucci, Luana Olivieri, Juan Sebastian Totero Gongora   +2 more
doaj   +1 more source

Perovskite Photodetectors at the Intelligence Frontier: From Tunable Materials to Adaptive Optoelectronic Systems

Carbon Energy, EarlyView.
This comprehensive review presents a progressive roadmap for perovskite vision detectors. Centered on perovskite‐based artificial perception, the graphic illustrates a systematic evolution: starting with fundamental material engineering and device architectures, advancing toward complex functional strategies such as flexible neuromorphic imaging ...
Chenglong Li, Wei Qu, Deepak Kumar, Naini Jain, Nur Wardina Syahirah binti Mohamad Fadil, Nur Najiha binti Ahmad Rasid, Emannuel Kymakis, Maria Vasilopoulou, Chunxiong Bao, Feng Gao, Peng Gao, Sanjeev Kumar Sharma, Mohammad Khaja Nazeeruddin, Abd. Rashid bin Mohd Yusoff, Haotong Wei   +14 more
wiley   +1 more source