Repository logo
English
  • English
  • Català
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Italiano
  • Latviešu
  • Magyar
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Suomi
  • Svenska
  • Türkçe
  • Tiếng Việt
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Yкраї́нська
  • Log In
    or
    New user? Click here to register.Have you forgotten your password?
Repository logo
  • Communities & Collections
  • All of R-3
English
  • English
  • Català
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Italiano
  • Latviešu
  • Magyar
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Suomi
  • Svenska
  • Türkçe
  • Tiếng Việt
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Yкраї́нська
  • Log In
    or
    New user? Click here to register.Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Rosemblun, Marcela Laura"

Now showing 1 - 1 of 1
Results Per Page
Sort Options
  • Loading...
    Thumbnail Image
    Item
    Automatic differentiation: Overview and application to systems of parameterized nonlinear equations
    (1993) Rosemblun, Marcela Laura; Dennis, John E., Jr.
    Automatic Differentiation is a computational technique that allows the evaluation of derivatives of functions defined by computer programs. Derivatives are calculated by applying the chain rule of differential calculus to the sequence of elementary computations involved in the program. In this work, an overview of the theory and implementation of automatic differentiation is presented, as well as a description of the available software. An application of automatic differentiation in the context of solving systems of parameterized nonlinear equations is discussed. In this application, the "differentiated" functions are implementations of Newton's method and Broyden's method. The iterates generated by the algorithms are differentiated with respect to the parameters. The results show that whenever the sequence of iterates converges to a solution of the system, the corresponding sequence of derivatives (computed by automatic differentiation) also converges to the correct value. Additionally, we show that the "differentiated" algorithms can be successfully employed in the solution of parameter identification problems via the Black-Box method.
  • About R-3
  • Report a Digital Accessibility Issue
  • Request Accessible Formats
  • Fondren Library
  • Contact Us
  • FAQ
  • Privacy Notice
  • R-3 Policies

Physical Address:

6100 Main Street, Houston, Texas 77005

Mailing Address:

MS-44, P.O.BOX 1892, Houston, Texas 77251-1892