Results 91 to 100 of about 166,726 (252)

Reproducing Kernels for Visual Surface Interpolation. [PDF]

, 1985
We examine the details of two related methods for the recovery of virtual surfaces from space depth data. The methods use the reproducing kernels of Hilbert spaces to construct a spline interpolating the data. such that this spline is of minimal norm. We
Boult, Terrance E.
core   +1 more source

Analog Tensor Processing With Carbon Nanotube In‐Memory Matrix Multiplications for Edge Computer Vision Acceleration

Advanced Materials, EarlyView.
This work prototypes a carbon nanotube‐based analog tensor core that performs in‐memory, parallel visual processing. Integrating non‐volatile memories and compact circuits, the core enables high‐speed analog matrix multiplications and can demonstrate accurate three dimensional (3D) spatial transformation and edge detection. With lightweight design, the
Jingfang Pei, Lekai Song, Songwei Liu, Yingyi Wen, Yaoqiang Zhou, Yang Liu, Pengyu Liu, Wenyu Cui, Xin Lu, Teng Ma, Zegao Wang, Guohua Hu   +11 more
wiley   +1 more source

General construction of reproducing kernels on a quaternionic Hilbert space

, 2017
A general theory of reproducing kernels and reproducing kernel Hilbert spaces on a right quaternionic Hilbert space is presented. Positive operator-valued measures and their connection to a class of generalized quaternionic coherent states are examined.
S. Twareque Ali, K. Thirulogasanthar
core   +1 more source

Defect‐Templated Phase Engineering in Atomically Thin Metals

Advanced Materials, EarlyView.
Graphene defects are transformed from passive imperfections into programmable templates for phase‐selective growth of atomically thin silver. Plasma‐generated boundary defects favor Ag(1), whereas sp3‐rich zero‐layer graphene promotes Ag(2). This defect‐directed intercalation links local graphene chemistry to crystalline phase, electronic structure ...
Arpit Jain, Boyang Zheng, Sawani Datta, Kanchan Ulman, Jakob Henz, Matthew Wei‐Jun Liu, Van Dong Pham, Wen He, Chengye Dong, Li‐Syuan Lu, Alexander Vera, Nader Sawtarie, Wesley Auker, Ke Wang, Bob Hengstebeck, Zachary W. Henshaw, Shreya Mathela, Maxwell Wetherington, William H. Blades, Kenneth Knappenberger, Ursula Wurstbauer, Su Ying Quek, Ulrich Starke, Shengxi Huang, Vincent H. Crespi, Joshua A. Robinson   +25 more
wiley   +1 more source

Atomically Precise Ag11 and Ag12 Nanocluster‐Assembled 2D Materials for Memristive and Neuromorphic Functionality

Advanced Materials, EarlyView.
Two‐dimensional Ag11 and Ag12 cluster‐assembled materials (CAMs) are synthesized, offering atomically precise platforms with tunable electronic properties. The resulting materials exhibit robust memristive switching and neuromorphic response, demonstrating their promise for advanced nanoelectronic and memory applications.
Noohul Alam, Towhidur Rahaman, Céline Besnard, Arnulf Rosspeintner, Latevi Max Lawson Daku, Saood Khan, Soumya Jyoti Ray, Thomas Bürgi   +7 more
wiley   +1 more source

Representation by Integrating Reproducing Kernels

, 2012
Based on direct integrals, a framework allowing to integrate a parametrised family of re-producing kernels with respect to some measure on the parameter space is developed.
Thomas Hotz, Fabian J. E. Telschow
core  

Prediction performance of DMD with reproducing kernels.

, 2018
This plot shows the error of naive Bayes classifier for success or failure of the shot, using the DMD with reproducing kernels (red), the DMD (blue), and the maximum values (black) inputting various input matrices.
Yoshinobu Kawahara (5931479), Takeshi Kawasaki (431845), Yuki Inaba (5931476), Keisuke Fujii (3982910)   +3 more
core   +1 more source

Descriptors to Dynamics: A Materials and Device Perspective on in‐Materio Physical Reservoir Computing for Neuromorphic Edge Intelligence

Advanced Materials, EarlyView.
Intrinsic material dynamics are harnessed as computational resources for neuromorphic in‐materio physical reservoir computing. Defects, ionic motion, interfaces, percolation, geometry, and biasing shape transient states that provide fading memory, nonlinearity, and high‐dimensional projection for simple readout. A descriptor‐to‐dynamics framework links
Kshitij RB Singh, Alif Syafiq Kamarol Zaman, Muzhen Xu, Yuki Usami, Saptarshi Das, Hirofumi Tanaka   +5 more
wiley   +1 more source

A probabilistic framework for mismatch and profile string kernels

, 2005
There has recently been numerous applications of kernel methods in the field of bioinformatics. In particular, the problem of protein homology has served as a benchmark for the performance of many new kernels which operate directly on strings (such as ...
Vinokourov, A., Saunders, C. J., Soklakov, A. N.   +2 more
core   +1 more source

Privacy-Preserving Classification of Vertically Partitioned Data via Random Kernels [PDF]

, 2007
We propose a novel privacy-preserving support vector machine (SVM) classifier for a data matrix A whose input feature columns are divided into groups belonging to different entities.
Mangasarian, Olvi, Fung, Glenn, Wild, Edward   +2 more
core