New Networks for Linear Programming

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概要

• 論文の詳細を見る

• We propose a set of new algorithms for linear programming. These algorithms are derived by accelerating the method of averaged convex projections for linear inequalities. We provide strict proofs for the convergence of our algorithms. The algorithms are so simple that they can be calculated by super-parallel processing. To this effect, we propose networks for implementing the algorithms. Furthermore, we provide illustrative examples to demonstrate the capability of our algorithms.

• 社団法人電子情報通信学会の論文
• 1998-05-25

著者

• Yamashita Y

  Tokyo Inst. Technol. Tokyo Jpn

• YAMASHITA Yukihiko

  the Faculty of Engineering, Tokyo Institute of Technology

関連論文

• Paley-Wiener Multiresolution Analysis and Paley-Wiener Wavelet Frame
• General Frame Multiresolution Analysis and Its Wavelet Frame Representation
• New Networks for Linear Programming

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