Datasets

subject: Computer Science type: dataset date: 2016

Total is 71 Results
OPCBSPL: Orthogonal polynomials relative to cardinal B-spline weight functions

10.4231/R7NG4NKC

Walter Gautschi ORCID logo

10/28/2016

A stable and efficient discretization procedure is developed to compute recurrence coefficients for orthogonal polynomials whose weight function is a polynomial cardinal B-spline of order greater than, or equal to, one.

B-spline Computer Science Mathematics Modification algorithms for orthogonal polynomials Orthogonal polynomials polynomials Walter Gautschi Archives weight functions

Code and Dataset for Pattern Recognition Benchmarks

10.4231/R7610X8M

Jonas Hepp , Mireille Boutin ORCID logo , Yellamraju Tarun

02/03/2016

This code computed a sequence of bounds for the error rate of a pattern recognition method. The bounds correspond to the error rate that one would expect to achieve by simply selecting features at random and thresholding the feature (TARP) approach.

classification Computer Science Electrical and Computer Engineering feature evaluation image processing image recognition Pattern Recognition Pedestrian Classification

32-digit values of the first 100 recurrence coefficients for an Airy weight function

10.4231/R7V122R6

Walter Gautschi ORCID logo

10/19/2016

32-digit values of the first 100 recurrence coefficients for the (normalized) weight function w(x)=c*x^(-5/6)e^(-x)Ai((3x/2)^(2/3)) on [0,Inf], c=2^(-1/6)*3^(1/6)/pi^(1/2), where Ai is the Airy function

Airy weight function Computer Science Mathematics Modification algorithms for orthogonal polynomials Orthogonal polynomials Quadrature and cubature formulas Walter Gautschi Archives

Scripts for a discrete top-down Markov problem in approximation theory

10.4231/R74Q7RX0

Walter Gautschi ORCID logo

10/04/2016

Matlab scripts for a discrete top-down Markov problem in approximation theory

approximation theory Computer Science Mathematics polynomials Walter Gautschi Archives

Code and Dataset for Pattern Recognition Benchmarks

10.4231/R7G73BPN

Jonas Hepp , Mireille Boutin ORCID logo , Yellamraju Tarun

12/12/2016

This code computed a sequence of bounds for the error rate of a pattern recognition method. The bounds correspond to the error rate that one would expect to achieve by simply selecting features at random and thresholding the feature (TARP) approach.

classification Computer Science Electrical and Computer Engineering feature evaluation image processing image recognition Pattern Recognition Pedestrian Classification

32-digit values of the first 100 recurrence coefficients for the Fermi-Dirac-type weight function with exponent r=2

10.4231/R77S7KR9

Walter Gautschi ORCID logo

12/09/2016

32-digit values of the first 100 recurrence coefficients for orthogonal polynomials relative to the weight function w(x)=[1/(exp(x)+1)]^r on [0,Inf], r=2

Computer Science Mathematics Modification algorithms for orthogonal polynomials Orthogonal polynomials Walter Gautschi Archives weight functions

32-digit values of the first 100 recurrence coefficients for the Fermi-Dirac-type weight function with exponent r=4

10.4231/R708639Z

Walter Gautschi ORCID logo

12/09/2016

32-digit values of the first 100 recurrence coefficients for orthogonal polynomials relative to the weight function w(x)=[1/(exp(x)+1)]^r on [0,Inf], r=4

Computer Science Mathematics Modification algorithms for orthogonal polynomials Orthogonal polynomials Walter Gautschi Archives weight functions

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