Results 251 to 260 of about 6,019,459 (297)

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

“Smelltronics”—From Gas to Smell Sensing

Advanced Materials, EarlyView.
The emerging field of smelltronics, encompassing sensing technologies for complex volatile organic compounds, holds significant potential for extracting valuable chemical information. It facilitates the noninvasive, real‐time monitoring of humans, food, and the environment.
Takeshi Ono, Tsunaki Takahashi, Jiangyang Liu, Haruka Honda, Zeng Jing, Wataru Tanaka, Takuro Hosomi, Takeshi Yanagida   +7 more
wiley   +1 more source

Phase Engineering of Atomically Precise Nanoclusters (APNCs) of Gold and Beyond

Advanced Materials, EarlyView.
Engineering the structural phase of materials is of paramount importance for both fundamental research and practical applications. In this Review, we summarize the recent progress in controlling the phases of atomically precise nanoclusters (APNCs) of gold, silver and copper, as well as bimetallic systems. The phase‐enabled material properties of APNCs
Yitong Wang, Avirup Sardar, Weijie Ji, Zhongyu Liu, Rongchao Jin   +4 more
wiley   +1 more source

A Multilinear Singular Value Decomposition [PDF]

SIAM Journal on Matrix Analysis and Applications, 2000
This paper investigates higher order singular value decompositions (HOSVD) as multilinear generalization of singular value decomposition (SVD), in terms of higher order tensors exhibiting symmetries as motivated by applications in higher order statistics. This includes matrix representation of higher order tensors, their rank properties, generalization
Lieven De Lathauwer, Joos Vandewalle
exaly   +4 more sources

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Singular Value Assignment

SIAM Journal on Control and Optimization, 2009
We give a necessary and sufficient condition for the existence of a matrix $F$ such that the singular values of $A+BF$ are the prescribed values. We also give a simple algorithm to compute $F$ if the prescribed values satisfy the condition.
Clyde F. Martin, Xiaochang A. Wang
openaire   +1 more source

Downdating the Singular Value Decomposition

SIAM Journal on Matrix Analysis and Applications, 1995
Let \(A\) be a matrix with known singular values and left and/or right singular vectors, and let \(A'\) be the matrix obtained by deleting a row from \(A\). Computing the singular value decomposition (SVD) of \(A'\) from the SVD of \(A\) is called the downdating singular value decomposition problem (DSVDP).
Ming Gu 0002, Stanley C. Eisenstat
openaire   +1 more source

Computing the Structured Singular Value

SIAM Journal on Matrix Analysis and Applications, 1992
Discussing some problems of multivariable control theory, the author begins to examine some algorithms to compute the structured singular value due to \textit{J. C. Doyle} [Analysis of feedback systems with structured uncertainties. Proc. IEE-D 129, No. 6, 246-250 (1982; MR 84a:93035)]; this notion, in particular, includes the largest singular value of
openaire   +2 more sources

Singular value features of images

SPIE Proceedings, 2000
This paper presents the preliminary results of our investigation on using singular value decomposition transform to extract effective image features. It proposes using the singular values of subimages to discriminate different classes of imagery.
Jingxin Zhang 0001, Jim Schroeder 0001, Tristrom Cooke, Nicholas J. Redding, Tahong Tang   +4 more
openaire   +2 more sources

Continuation of Singular Value Decompositions

Mediterranean Journal of Mathematics, 2005
In this work we consider computing a smooth path for a (block) singular value decomposition of a full rank matrix valued function. We give new theoretical results and then introduce and implement several algorithms to compute a smooth path. We illustrate performance of the algorithms with a few numerical examples.
L. DIECI L, GASPARO, MARIA GRAZIA, PAPINI, ALESSANDRA   +2 more
openaire   +1 more source