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Another Simple Recurrent Neural Network for Quadratic and Linear Programming

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Advances in Neural Networks – ISNN 2009 (ISNN 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5553))

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Abstract

A new recurrent neural network is proposed for solving quadratic and linear programming problems, which is derived from two salient existing neural networks. One of the predecessors has lower structural complexity but were not shown to be capable of solving degenerate QP problems including LP problems while the other does not have this limitation but has higer structural complexity. The proposed model inherits the merits of both models and thus serves as a competitive alternative for solving QP and LP problems. Numerical simulations are provided to demonstrate the performance of the model and validate the theoretical results.

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Author information

Authors and Affiliations

  1. State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology (TNList), Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China

    Xiaolin Hu & Bo Zhang

Authors
  1. Xiaolin Hu
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  2. Bo Zhang
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Editor information

Editors and Affiliations

  1. Departamento de Control Automático, CINVESTAV-IPN, A.P. 14-740, Av.IPN 2508, 07360, México D.F., México

    Wen Yu

  2. Deptartment of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, USA

    Haibo He

  3. Dept. of Electrical and Computer Engineering, South Dakota School of Mines & Technology, 501 E. St. Joseph Street, SD 57701, Rapid City, USA

    Nian Zhang

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© 2009 Springer-Verlag Berlin Heidelberg

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Hu, X., Zhang, B. (2009). Another Simple Recurrent Neural Network for Quadratic and Linear Programming. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5553. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01513-7_13

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  • DOI: https://doi.org/10.1007/978-3-642-01513-7_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01512-0

  • Online ISBN: 978-3-642-01513-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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