Results 51 to 60 of about 14,201 (261)

Fast Convolutional Sparse Coding [PDF]

open access: yes2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013
Sparse coding has become an increasingly popular method in learning and vision for a variety of classification, reconstruction and coding tasks. The canonical approach intrinsically assumes independence between observations during learning. For many natural signals however, sparse coding is applied to sub-elements ( i.e.
Hilton Bristow   +2 more
openaire   +4 more sources

Microscopic Insights into Magnetic Warping and Time‐Reversal Symmetry Breaking in Topological Surface States of Rare‐Earth‐Doped Bi2Te3

open access: yesAdvanced Materials, EarlyView.
Magnetic doping of the topological insulator Bi2Te3 with erbium adatoms induces out‐of‐plane magnetism and breaks time‐reversal symmetry, opening a Dirac gap and driving a Fermi surface transition from hexagonal to star‐of‐David geometry. Microscopy, spectroscopy, and magnetic dichroism reveal atomically controlled magnetic interactions that tailor the
Beatriz Muñiz Cano   +18 more
wiley   +1 more source

Convolutional Codes of Goppa Type [PDF]

open access: yesApplicable Algebra in Engineering, Communication and Computing, 2004
A new kind of Convolutional Codes generalizing Goppa Codes is proposed. This provides a systematic method for constructing convolutional codes with prefixed properties. In particular, examples of Maximum-Distance Separable (MDS) convolutional codes are obtained.
Domínguez Pérez, José Ángel   +2 more
openaire   +4 more sources

Energetic Offset in Organic Solar Cells‐ Importance, Confusion and Outlook

open access: yesAdvanced Materials, EarlyView.
Energetic offsets in organic solar cells (OSCs) remain a subject of debate due to measurement‐ and lab‐dependent discrepancies. This Perspective clarifies the physical origins of these variations and identifies temperature‐dependent electro‐optical methods as a reliable approach to obtain consistent offset values.
Nakul Jain   +5 more
wiley   +1 more source

On Doubly-Cyclic Convolutional Codes [PDF]

open access: yesApplicable Algebra in Engineering, Communication and Computing, 2006
Cyclicity of a convolutional code (CC) is relying on a nontrivial automorphism of the algebra F[x]/(x^n-1), where F is a finite field. If this automorphism itself has certain specific cyclicity properties one is lead to the class of doubly-cyclic CC's. Within this large class Reed-Solomon and BCH convolutional codes can be defined.
Gluesing-Luerssen, H, Schmale, W
openaire   +4 more sources

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

open access: yesAdvanced Materials, EarlyView.
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley   +1 more source

ANÁLISIS DEL DESEMPEÑO DE ESQUEMAS CODIFICACIÓN TURBO Y CONVOLUCIONAL EN EL ENLACE DE BAJADA DE LTE-ADVANCED

open access: yesRevista Politécnica, 2017
This article presents a comparative performance analysis of the turbo and convolutional encoders applicable to LTE-A Downlink, access technology that is booming in the region.
Juan Rodríguez   +3 more
doaj   +1 more source

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

open access: yesAdvanced 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   +8 more
wiley   +1 more source

Strongly-MDS convolutional codes [PDF]

open access: yesIEEE Transactions on Information Theory, 2006
33 ...
Heide Gluesing-Luerssen   +2 more
openaire   +3 more sources

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

open access: yesAdvanced 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   +3 more
wiley   +1 more source

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