Estimation of Distributed Generation Using Complex-Valued Network Inversion with Regularization

  • Takehiko Ogawa
  • Kyosuke Nakamura
  • Hajime Kanada
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 110)


Network inversion has been studied as a neural network based solution of inverse problems. Complex-valued network inversion has been proposed as the extension of this inversion to the complex domain. Further, regularization is considered for solving ill-posed inverse problems. On the other hand, the estimation of the parameters of a distributed generation from observed data is a complex-valued inverse problem with ill-posedness. In this chapter, we propose the application of a complex-valued network inversion with regularization to the inverse estimation of a distributed generation.


Complex-valued neural networks Distributed generation Ill-posed inverse problems Regularization 



This work was supported in part by a Grant-in-Aid for Scientific Research #21700260 from the Japan Society for the Promotion of Science.


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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Takehiko Ogawa
    • 1
  • Kyosuke Nakamura
    • 2
  • Hajime Kanada
    • 1
  1. 1.Department of Electronics and Computer SystemsTakushoku UniversityHachioji-shiJapan
  2. 2.Electronics and Information Science Course, Graduate School of EngineeringTakushoku UniversityHachioji-shiJapan

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