Subject
- Computer Science 64
- Mathematics 64
- Biomedical Engineering 8
- Agriculture 3
- Mechanical Engineering 3
- Earth and Atmospheric Sciences 2
- Aeronautics and Astronautics Engineering 1
- Nuclear Engineering 1
- Physics 1
Creator
- Walter Gautschi, 0000-0001-9184-8899 64
- Pavlos Vlachos, 0000-0002-8040-9257 7
- Michael Markl 5
- Susanne Schnell 5
- Vitaliy Rayz 5
- Benjamin Dickerhoff 4
- David Saloner 4
- Melissa Brindise 4
- Qianlai Zhuang, 0000-0002-4536-9851 4
- Sean Rothenberger, 0000-0003-1341-6147 4
Type
- Dataset 91
Date
Total is 91 Results
32-digit values of the first 100 recurrence coefficients for the Bose-Einstein weight function
10.4231/R7MG7MGF
11/30/2016
32-digit values of the first 100 recurrence coefficients for the weight function w(x)=[x/(exp(x)-1)]^r on [0,Inf], r=1
Bose-Einstein distribution Computer Science Equation Table Gaussian quadrature Mathematics Matlab OPQ routine Orthogonal polynomials Quadrature and cubature formulas Walter Gautschi Archives
32-digit values of the first 100 recurrence coefficients for the Bose-Einstein-type weight function with exponent 2
10.4231/R7GQ6VQ8
11/30/2016
32-digit values of the first 100 recurrence coefficients for the weight function w(x)=[x/(exp(x)-1)]^r on [0,Inf], r=2
Bose-Einstein distribution Computer Science Equation Table Gaussian quadrature Mathematics Matlab OPQ routine Orthogonal polynomials Walter Gautschi Archives
32-digit values of the first 100 recurrence coefficients for the Bose-Einstein-type weight function with exponent 3
10.4231/R7BZ640B
11/29/2016
32-digit values of the first 100 recurrence coefficients for the weight function w(x)=[x/(exp(x)-1)]^r on [0,Inf], r=3
Bose-Einstein distribution Computer Science Equation Table Gaussian quadrature Mathematics Matlab OPQ routine Orthogonal polynomials Walter Gautschi Archives
32-digit values of the first 100 recurrence coefficients for the Bose-Einstein-type weight function with exponent 4
10.4231/R7765C8X
11/29/2016
32-digit values of the first 100 recurrence coefficients for the weight function w(x)=[x/(exp(x)-1)]^r on [0,Inf], r=4
Bose-Einstein distribution Computer Science Equation Table Gaussian quadrature Mathematics Matlab OPQ routine Orthogonal polynomials Walter Gautschi Archives
32-digit values of the first 100 recurrence coefficients for the half-range generalized Hermite weight function with exponent 0
10.4231/R7ZP443R
11/29/2016
32-digit values of the first 100 recurrence coefficients for the weight function w(x)=x^(2*mu)*exp(-x^2) on [0,Inf], mu=0
Computational methods Computer Science Equation Table Gaussian quadrature Hermite weight function Hilbert Transforms Integral Transforms Mathematics Matlab Numerical integrations OPQ routine Orthogonal polynomials Walter Gautschi Archives
Loading variable-precision recurrence coefficients
10.4231/R7P26W3X
11/22/2016
Loading a text file of variable-precision recurrence coefficients into Matlab symbolic or double-precision arrays
Computer Science Jacobi weight functions Mathematics Matlab Modification algorithms for orthogonal polynomials Orthogonal polynomials Walter Gautschi Archives
Data for Permafrost Degradation Diminishes Terrestrial Ecosystem Carbon Sequestration Capacity on the Qinghai-Tibetan Plateau
10.4231/03FM-XN05
Dan Kou
,
Dongsheng Zhao
,
Du Zheng
,
Lei Liu
,
Qianlai Zhuang
,
Yuanhe Yang
09/17/2021
Dataset about the effects of permafrost degradation on C and N cycling on the Qinghai-Tibetan Plateau in the 21st century
Carbon Sequestration Climate Change Earth and Atmospheric Sciences Matlab Nitrogen Availability Permafrost degradation Qinghai-Tibetan Plateau
Input from torus longitudinalis drives binocularity and spatial summation in zebrafish optic tectum
10.4231/STQE-9A91
12/16/2021
In this study we demonstrate that torus longitudinalis feedback projections to tectum drive binocular integration and spatial summation in a defined tectal circuit. These findings reveal a novel role for the zebrafish torus longitudinalis.
biological sciences fluorescence microscopy Matlab Neuroscience research Vision zebrafish
Evaluating the variability of surface soil moisture simulated within CMIP5 using SMAP data
10.4231/A0QC-7E03
Pierre Gentine
,
Qianlai Zhuang
,
Seungbum Kim
,
Xuan Xi
12/01/2021
This dataset includes the comparison results of 17 land surface models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) globally using the Soil Moisture Active Passive (SMAP) products and codes for analysis.
EAPS Fourier Analysis Land Surface Model Matlab SMAP Soil Moisture
Combine Kart Truck GPS Data Archive
10.4231/XBG9-P763
James Krogmeier
,
Yaguang Zhang
12/09/2021
GPS data for agricultural vehicles collected during wheat harvesting.
Activity Recognition Agriculture Digital Agriculture Electrical and Computer Engineering Field Shape GPS Matlab Traceability Wheat Harvesting
Display #
Results 11 - 20 of 91