A Parallel Quasi-Newton Method for Gaussian Data Fitting
نویسندگان
چکیده
We describe a parallel method for unconstrained optimization based on the quasi-Newton descent method of Broyden, Fletcher, Goldfarb, and Shanno. Our algorithm is suitable for both single-instruction and multiple-instruction parallel architectures and has only linear memory requirements in the number of parameters used to ®t the data. We also present the results of numerical testing on both single and multiple Gaussian data ®tting problems. Ó 1998 Published by Elsevier Science B.V. All rights reserved.
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عنوان ژورنال:
- Parallel Computing
دوره 24 شماره
صفحات -
تاریخ انتشار 1998