Results 121 to 130 of about 8,004 (293)

Affinity Preserving Quantization for Hashing: A Vector Quantization Approach to Learning Compact Binary Codes

open access: yes, 2016
Hashing techniques are powerful for approximate nearest neighbour (ANN) search.Existing quantization methods in hashing are all focused on scalar quantization (SQ) which is inferior in utilizing the inherent data distribution.In this paper, we propose a ...
Wang, Zhe   +3 more
core   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

open access: yesAdvanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho   +6 more
wiley   +1 more source

Aluminum‐Substituted Yttrium Iron Garnet Films With Perpendicular Anisotropy Grown on Silicon by Sputtering

open access: yesAdvanced Electronic Materials, EarlyView.
Ultrathin Al‐substituted YIG films with perpendicular magnetic anisotropy are sputter‐grown directly on Si/SiOx using an ultrathin AlOx buffer layer. Al diffusion reduces the saturation magnetization and stabilizes PMA via magnetoelastic effects. Pt/Al:YIG bilayers exhibit strong spin Hall magnetoresistance and efficient spin–orbit torque switching ...
Matteo Fettizio   +4 more
wiley   +1 more source

Configurable sparse matrix - matrix multiplication accelerator on FPGA: A systematic design space exploration approach with quantization effects

open access: yesAlexandria Engineering Journal
High-performance sparse matrix multipliers are essential for deep learning applications, and as big data analytics continues to evolve, specialized accelerators are also needed to efficiently handle sparse matrix operations.
G. Noble   +3 more
doaj   +1 more source

Recent Advances in Programmable Metasurfaces and Meta‐Devices

open access: yesAdvanced Electronic Materials, EarlyView.
Programmable metasurfaces enable various novel functionalities by dynamically tuning electromagnetic wavefronts. This article provides a comprehensive review of recent advances in microwave and terahertz programmable metasurfaces, covering electrical, thermal, optical, and mechanical control mechanisms.
Linda Shao   +4 more
wiley   +1 more source

People Counting and Positioning Using Low‐Resolution Infrared Images for FeFET‐Based In‐Memory Computing

open access: yesAdvanced Electronic Materials, EarlyView.
In this work, low‐resolution infrared imaging is combined with a 28 nm FeFET IMC architecture to enable compact, energy‐efficient edge inference. MLC FeFET devices are experimentally characterized, and controlled multi‐level current accumulation is validated at crossbar array level.
Alptekin Vardar   +9 more
wiley   +1 more source

κ-Minkowski Spacetimes and DSR Algebras: Fresh Look and Old Problems

open access: yesSymmetry, Integrability and Geometry: Methods and Applications, 2010
Some classes of Deformed Special Relativity (DSR) theories are reconsidered within the Hopf algebraic formulation. For this purpose we shall explore a minimal framework of deformed Weyl-Heisenberg algebras provided by a smash product construction of DSR ...
Andrzej Borowiec, Anna Pachol
doaj   +1 more source

Topological Materials and Related Applications

open access: yesAdvanced Electronic Materials, EarlyView.
This review covers topological materials—including topological insulators, quantum valley Hall and quantum spin Hall insulators, and topological Weyl and Dirac semimetals—as well as their most recent advancements in fields such as spintronics, electronics, photonics, thermoelectrics, and catalysis.
Carlo Grazianetti   +9 more
wiley   +1 more source

From geometric quantization to Moyal quantization

open access: yes, 1995
We show how the Moyal product of phase-space functions, and the Weyl correspondence between symbols and operator kernels, may be obtained directly using the procedures of geometric quantization, applied to the symplectic groupoid constructed by "doubling"
Gracia Bondía, José M.   +3 more
core   +1 more source

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

open access: yesAdvanced 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   +10 more
wiley   +1 more source

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