© 1964 by British Computer Society
Function minimization by conjugate gradients
Electronic Computing Laboratory, The University, Leeds, UK
A quadratically convergent gradient method for locating an unconstrained local minimum of a function of several variables is described. Particular advantages are its simplicity and its modest demands on storage, space for only three vectors being required. An ALGOL procedure is presented, and the paper includes a discussion of results obtained by its used on various test functions.
* Electronic Computing Laboratory, The University, Leeds, 2.
![]()
CiteULike
Connotea
Del.icio.us What's this?
This article has been cited by other articles:
![]() |
W. S. DeSarbo, D. R. Lehmann, M. B. Holbrook, W. J. Havlena, and S. Gupta A Stochastic Three-Way Unfolding Model for Asymmetric Binary Data Applied Psychological Measurement, December 1, 1987; 11(4): 397 - 418. [Abstract] |
||||
![]() |
W. S. DeSarbo and D. L. Hoffman Simple and Weighted Unfolding Threshold Models for the Spatial Representation of Binary Choice Data Applied Psychological Measurement, September 1, 1986; 10(3): 247 - 264. [Abstract] |
||||
![]() |
W. S. DeSarbo, R. L. Oliver, and G. De Soete A Probabilistic Multidimensional Scaling Vector Model Applied Psychological Measurement, March 1, 1986; 10(1): 79 - 98. [Abstract] |
||||
![]() |
L. G. Birta and P. J. Trushel A comparative study of four implementations of a dynamic optimization scheme SIMULATION, August 1, 1969; 13(2): 89 - 97. [PDF] |
||||
![]() |
E. G. Gilbert A selected bibliography on parameter optimization methods suitable for hybrid computation SIMULATION, June 1, 1967; 8(6): 350 - 352. [PDF] |
||||

