10.4231/R7M043CX
12/12/2016
32-digit values of the first 100 recurrence coefficients for the weight function w(x)=x^a*exp(-x)*(x-1-log(x)) on [0,Inf], a=0
Computer Science Logarithmic weight functions Mathematics Modification algorithms for orthogonal polynomials Modified Chebyshev algorithm Orthogonal polynomials Walter Gautschi Archives weight functions
10.4231/R7SQ8XDM
12/05/2016
32-digit values of the first 100 recurrence coefficients for the weight function w(x)=x^a*exp(-x)*(x-1-log(x)) on [0,Inf], a=-1/2
Computer Science Gaussian quadrature Logarithmic weight functions Mathematics Modification algorithms for orthogonal polynomials Orthogonal polynomials Walter Gautschi Archives
10.4231/R7XG9P4B
12/05/2016
32-digit values of the first 100 recurrence coefficients for orthogonal polynomials relative to the weight function w(x)=phi_m(x) on [0,m], m=2
B-spline Computer Science Mathematics Modification algorithms for orthogonal polynomials Orthogonal polynomials Walter Gautschi Archives weight functions
10.4231/R78P5XHT
12/05/2016
32-digit values of the first 100 recurrence coefficients for the weight function w(x)=x^a*exp(-x)*(x-1-log(x)) on [0,Inf], a=1/2
Computer Science Gaussian quadrature Logarithmic weight functions Mathematics Modification algorithms for orthogonal polynomials Orthogonal polynomials Walter Gautschi Archives
10.4231/R72805KQ
12/06/2016
Variable-precision Matlab routine for generating the nodes and weights of a Gaussian quadrature rule
Computation of recurrence coefficients and special Gaussian quadrature rules Computer Science Gaussian quadrature Mathematics Walter Gautschi Archives weight functions
10.4231/R7NZ85NT
12/06/2016
32-digit values of the first 100 recurrence coefficients for the weight function w(x)=[log(1/x)]^b on [0,1], b=1/2
Computer Science Mathematics Modification algorithms for orthogonal polynomials moment-based method Orthogonal polynomials Walter Gautschi Archives weight functions
10.4231/R7DF6P63
Alexander M. Hainen , Andrew Sydelko , Darcy M. Bullock , David Burford , Michael Witt
12/09/2016
Two iconic buildings on the Purdue University campus, the Engineering Administration Building and the retired Heating and Power Plant-North, were targeted for demolition in 2012 to make way for the construction of the Wilmeth Active Learning Center.
Active Learning Center construction ALC Construction building construction Building Construction Management Civil Engineering ENADALC Purdue University WALC Wilmeth Active Learning Center
10.4231/R7J67DXD
Alexander M. Hainen , Andrew T. Sydelko , Darcy M. Bullock , David Burford , Michael Witt
12/09/2016
Two iconic buildings on the Purdue University campus, the Engineering Administration Building and the retired Heating and Power Plant-North, were targeted for demolition in 2012 to make way for the construction of the Wilmeth Active Learning Center.
Active Learning Center construction ALC Construction building construction Building Construction Management Civil Engineering construction time-lapse ENADALC Purdue University WALC Wilmeth Active Learning Center
10.4231/R7513W5P
Alexander M. Hainen , Andrew T. Sydelko , Darcy M. Bullock , David Burford , Michael Witt
12/09/2016
Two iconic buildings on the Purdue University campus, the Engineering Administration Building and the retired Heating and Power Plant-North, were targeted for demolition in 2012 to make way for the construction of the Wilmeth Active Learning Center.
Active Learning Center construction building construction Building Construction Management Civil Engineering construction time-lapse ENADALC Purdue University WALC Wilmeth Active Learning Center
10.4231/R7G73BPN
Jonas Hepp , Mireille Boutin , 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
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