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LIMITED MEMORY QUASI-NEWTON METHODS FOR NONLINEAR IMAGE RESTORATION

Published In: INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, ELECTRONICS AND ELECTRICAL TECHNOLOGY
Author(s): FARZIN MODARRES KHIYABANI

Abstract: Variational models of unconstrained optimization problems have been extremely successful in a wide variety of restoration problems, such as image restoration. In this paper, we present an efficient limited memory quasi-Newton (QN) technique to compute meaningful solutions for large-scale problems arising in some image restoration problems. Numerical experiments reveals the effectiveness of the proposed method particularly for images of large size.

  • Publication Date: 03-Aug-2014
  • DOI: 10.15224/978-1-63248-005-7-56
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NON-STANDARD APPROACHES OF EVOLUTIONARY ALGORITHMS IN THE EXPLORATION-EXPLOITATION DILEMMA

Published In: INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, ELECTRONICS AND ELECTRICAL TECHNOLOGY
Author(s): OSWALDO E. VELEZ-LANGS

Abstract: This critical-reflexive paper is based on the known problem presented in the Exploration-Exploitation Dilemma (EED) when working with Evolutionary Algorithms (EAs) and focusing on proposals that put forward, in this case, both a traditional ap-proach as well as more recent approaches that manage population solutions (individu-als) differently than the standard EAs, that is: The Learnable Evolutionary Model (LEM) and the Distribution Estimation Algorithms (DEA).

  • Publication Date: 03-Aug-2014
  • DOI: 10.15224/978-1-63248-005-7-57
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