Results 81 to 90 of about 15,373 (263)
A Tensor-Based Go Decomposition Method for Hyperspectral Anomaly Detection
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingHyperspectral anomaly detection (HAD) aims at effectively separating the anomaly target from the background. The low-rank and sparse matrix decomposition (LRaSMD) technique has shown great potential in HAD tasks.
Meiping Song +4 more
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Advanced Functional Materials, EarlyView.Dual‐cation site engineering unlocks stable and fast sodium storage in Na4VMn(PO4)3 cathodes. Li+ at Na2 suppresses Jahn‐Teller distortion, while K+ at Na1 expands ion channels, enabling synchronized V/Mn redox and quasi‐single‐phase kinetics. This atomic‐level strategy achieves ultralong cycling stability, high‐rate capability, and full cell viability
Jiaze Sun +8 more
wiley +1 more source
Co-PARAFAC: A Novel Cost-Efficient Scalable Tensor Decomposition Algorithm
IEEE AccessThis paper proposes a novel tensor decomposition method, cooperative parallel factor (Co-PARAFAC), that is devised to achieve higher accuracy with lower computational complexity and memory requirements than the conventional PARAFAC.
Farshad Shams +2 more
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Advanced Functional Materials, EarlyView.PTFE nanoparticle–anchored rGO (rGO@PTFE) for scalable solvent‐free fabrication of ultra‐thick, high‐density cathodes, achieving high conductivity (9.55 S cm−1), lithium transference (0.73), and improved wettability, is developed. The resulting cathode delivers 15.2 mAh cm−2 areal and 563 mAh cm−3 volumetric capacities, with full cells exhibiting 637 ...
Juhee Yoon +7 more
wiley +1 more source
Block Copolymers: Emerging Building Blocks for Additive Manufacturing
Advanced Functional Materials, EarlyView.This review addresses how block copolymer (BCP) physics and rheology have led to the widespread use of BCPs in advanced additive manufacturing techniques, with particular emphasis on the untapped potential of these nanostructured materials toward achieving multi‐scale architected materials with unique, programmable material properties.
Alice S. Fergerson +3 more
wiley +1 more source
Advanced Functional Materials, EarlyView.A machine learning and simulation‐guided strategy is demonstrated for gentle, non‐sonication dispersion of carbon nanotubes, preserving structural integrity and performance. This approach enables transparent conductive films with low sheet resistance, high transmittance, and sub‐20 µm printability.
Ying Zhou +7 more
wiley +1 more source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingThe structure information of hyperspectral image (HSI) is well-characterized by tensors, surpassing the capabilities of traditional compressive sensing reconstruction models based on vectors and matrices.
Xinwei Wan +4 more
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An Alternating Bayesian Approach to PARAFAC Decomposition of Tensors
IEEE Access, 2018 The PARAllel FACtor (PARAFAC) decomposition is known as one of the most commonly used tools in tensor signal/data processing. Unfortunately, its classical algorithms barely take the potential statistical and/or deterministic prior information of the ...
Ming Shi, Dan Li, Jian Qiu Zhang
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Advanced Functional Materials, EarlyView.This study demonstrates coherent control of 15N nuclear spins coupled to VB−${\text{V}}_{\text{B}}^{-}$ centers in isotope‐enriched hexagonal boron nitride. Selective addressing via spin‐state mixing enables Rabi driving, quantum gates, and coherence times exceeding 10 μs$\umu{\rm s}$.
Adalbert Tibiássy +6 more
wiley +1 more source
Hyperspectral Image Denoising With Group Sparse and Low-Rank Tensor Decomposition
IEEE Access, 2018 Hyperspectral image (HSI) is usually corrupted by various types of noise, including Gaussian noise, impulse noise, stripes, deadlines, and so on. Recently, sparse and low-rank matrix decomposition (SLRMD) has demonstrated to be an effective tool in HSI ...
Zhihong Huang +4 more
doaj +1 more source