Datasets

subject: Computer Science date: 2016

Total is 71 Results
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

Jacobi polynomials

10.4231/R7PR7SZ5

Walter Gautschi ORCID logo

12/15/2016

Matlab routines for the first N recurrence coefficients of Jacobi polynomials

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

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