Results 81 to 90 of about 5,098 (214)
Small, EarlyView.Grain‐size‐controlled resistive switching memory arrays based on Sn‐halide perovskite thin films are realized via a photo‐thermochemical process that creates lateral grain‐size gradients. The arrays exhibit domain‐specific volatile threshold switching and short‐term neural dynamics, enabling nonlinear conductance, tunable relaxation, integrate‐and‐fire,
Dohyung Kim +4 more
wiley +1 more source
Aircraft Target Classification Based on Correlation Features from Time-domain Echoes
, 2015 This paper reports the classification of helicopters, propeller-driven aircraft, and turbojet based on differences in their time-domain modulation periods using a conventional radar system.
Li Lin-sen +4 more
core +1 more source
In Vitro Reconstruction of Axonal Heat Sensing with a Photothermal Nerve‐on‐a‐Chip
Small, EarlyView.A photothermal nerve‐on‐a‐chip platform is presented that enables precise, localized heating of sensory axons with simultaneous electrical recording. The system reveals millisecond‐scale dynamics of heat‐evoked neural activity and provides a new approach to study how temperature‐dependent ion channel behavior is translated into axonal firing.
Koji Sakai +6 more
wiley +1 more source
, 2011 Full metadata records and copyright statements for publications contained in this portfolio thesis are available at the identifiers listedThree clinical investigations together with a combined editorial and review of the cardiovascular physiology of ...
Sharwood-Smith, Geoffrey H. +1 more
core
A Bilayer Rare‐Earth/High‐κ Oxide Memristor for Energy‐Efficient Neuromorphic Intelligence
Small, EarlyView.Interface‐engineered Gd2O3/HfO2 bilayer memristors demonstrate controlled filament formation, ultralow switching energy (∼13.56 pJ), and fast operation (∼350 ns) with a high ON/OFF ratio (∼107). The devices exhibit stable analog synaptic behavior and enable pattern recognition on Fashion‐MNIST, underscoring their promise for energy‐efficient ...
Hammad Ghazanfar +8 more
wiley +1 more source
Automatic Modulation Classification Using Compressive Convolutional Neural Network
, 2019 The deep convolutional neural network has strong representative ability, which can learn latent information repeatedly from signal samples and improve the accuracy of automatic modulation classification (AMC).
Li, Zening +6 more
core
Structural, Compositional, and Dielectric State Profiling in Label‐Free Single‐Cell Monitoring
Small Methods, EarlyView.Label‐free single‐cell monitoring leverages distinct physical interactions to access structural, compositional, and dielectric states of cells, enabling non‐perturbative, repeatable, and information‐rich measurements across diverse biological contexts. This review organizes representative platforms by intrinsic state variables and connects measurement ...
Changi Baek +6 more
wiley +1 more source
The Chemical Record, EarlyView.The transport properties and electrochemical reactivity of protic ionic liquids (ILs) are compared with those of aprotic analogs. Protic ILs are characterized by strong cation–anion hydrogen bonding and labile protons, enabling proton conduction and highlighting their potential as fuel cell electrolytes.
Masayoshi Watanabe, Seiji Tsuzuki
wiley +1 more source
Deep-learning based pulse repetition interval modulation classification and recognition
Pulse Repetition Interval (PRI) which represents the time interval between 2 consecutive emitted radar pulses, plays an important role in various signal processing applications especially in an electronic warfare environment when an accurate ...
Quek, Alston Bing Xuan
core
Multi-stage Learning for Radar Pulse Activity Segmentation
, 2023 Radio signal recognition is a crucial function in electronic warfare. Precise identification and localisation of radar pulse activities are required by electronic warfare systems to produce effective countermeasures. Despite the importance of these tasks,
Martin, Terrence +4 more
core