Results 241 to 250 of about 8,736,056 (314)
Deep Learning-Based Intelligent Resource Management for Renewable Energy Engineering Projects. [PDF]
Yao Y.
europepmc +1 more source
Memristive‐Gated RC‐Delay Synaptic Transistors for Time‐Encoded Analog in‐Memory Computing
A Memristive‐Gated Transistor for Time‐Encoded Analog In‐Memory Computing — By exploiting the RC delay of a self‐rectifying interface‐type memristor, nonlinear I–V distortion is structurally bypassed, enabling 3‐bit nonvolatile memory, spike‐timing‐based analog encoding, and hardware‐calibrated reservoir‐computing validation within a unified device ...
Yun‐Seo Shin +7 more
wiley +1 more source
The physical realization of artificial neurons is a critical challenge for energy‐efficient neuromorphic computing. This review presents a comprehensive analysis of the evolution of artificial neuron implementations from conventional CMOS to emerging post‐CMOS technologies.
Kannan Udaya Mohanan +4 more
wiley +1 more source
A defect‐engineered Ag/Gd2O3:Nb2O5/Pt rare earth composite oxide memristor enables stable multilevel reservoir states through pulse driven conductance modulation. Experimentally measured device responses are incorporated into a device aware reservoir computing framework for CIFAR‐100 image classification, highlighting the potential of rare earth ...
Hammad Ghazanfar +9 more
wiley +1 more source
Subject-Specific Deep Learning Model for Motor Imagery Direction Decoding. [PDF]
Parashiva PK, Kutteri SG, Vinod AP.
europepmc +1 more source
Kinetics‐Controlled Architecture of Binder‐Free Organic Electrodes for Enhanced Ion Transport
Pulse reverse electrodeposition controls nucleation and growth to create hierarchically porous Py‐derived oligomeric electrodes with enhanced ionic accessibility and reduced transport resistance. The resulting binder‐free architectures translate these transport advantages into practical sodium‐storage functionality.
Satendra Kumar +1 more
wiley +1 more source
Test-fairness deep learning with influence score. [PDF]
Wu JC +5 more
europepmc +1 more source
Physics‐Grounded Materials Artificial Intelligence for Reliable Materials Discovery
Physics‐Grounded Materials AI (PhysMat AI) integrates physical priors, descriptors, constraints, verification, and data infrastructure into a unified full‐stack framework, enabling reliable, interpretable, and autonomous AI‐driven materials discovery.
Yuhang Wang +3 more
wiley +1 more source

