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  Browse All Reviews > Mathematics Of Computing (G) > Numerical Analysis (G.1) > Approximation (G.1.2) > Least Squares Approximation (G.1.2...)  
 
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  1-7 of 7 Reviews about "Least Squares Approximation (G.1.2...)": Date Reviewed
  Continuous CMAC-QRLS and its systolic array
Qin T., Zhang H., Chen Z., Xiang W. Neural Processing Letters 22(1): 1-16, 2005.  Type: Article

The cerebellar model articulation controller (CMAC) was proposed in the 1970s by Albus [1] as a flexible design for controllers of devices, such as articulated robotic arms. The flexibility comes mainly from the learning capability of ...

Apr 19 2006
  Least squares convex-concave data smoothing
Demetriou I. Computational Optimization and Applications 29(2): 197-217, 2004.  Type: Article

A method for least squares convex-concave data smoothing is presented that may find application to problems where the data suggest that the shape of the underlying function is sigmoid. The author has developed an algorithm that, by usi...

Aug 2 2005
   Orthogonal least squares algorithm for the approximation of a map and its derivatives with a RBF network
Drioli C., Rocchesso D. Signal Processing 83(2): 283-296, 2003.  Type: Article

Radial basis functions are used for fitting a function and its derivatives. The method presented builds on the established orthogonal least squares approach with the additional inclusion of derivative data....

Jun 11 2003
  Partial linearization of one class of the nonlinear total least squares problem by using the inverse model function
Jukić D., Scitovski R., Späth H. Computing 62(2): 163-178, 1999.  Type: Article

The total least squares (TLS) problem is studied for a special class of models that have the form of the inverse of a continuous one-to-one function. The parameters a and b to be found in a least s...

Aug 1 1999
  Algorithm 742: L2CXFT: a Fortran subroutine for least-squares data fitting with nonnegative second divided differences
Demetriou I. ACM Transactions on Mathematical Software 21(1): 98-110, 1995.  Type: Article

Demetriou describes an implementation in Fortran 77 of Demetriou and Powell’s algorithm to fit data contaminated with random errors to a convex function. The technique first approximates a solution, then uses quadratic progra...

May 1 1996
  Optimal absolute error starting values for Newton-Raphson calculation of square root
Montuschi P., Mezzalama M. Computing 46(1): 67-86, 1991.  Type: Article

The authors address the problem of finding optimal starting values in terms of absolute error for Newton’s method when it is applied to finding square roots. This absolute error approach, as compared to the more extensively s...

Oct 1 1991
  Numerical aspects of the generalized CG-method applied to least squares problems
Evans D., Li C. Computing 41(1-2): 171-178, 1989.  Type: Article

The authors present a useful comparison between the generalized conjugate gradient method and an adjusted form of this method and the successive over-relaxation (SOR) and the conjugate gradient (CG) methods when applied to least square...

Jan 1 1990
 
 
 
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