Rates of convergence of the recursive radial basis function networks

نویسندگان

  • Janusz Mazurek
  • Adam Krzyzak
  • Andrzej Cichocki
چکیده

Recursive radial basis function (RRBF) neural networks are introduced and discussed. We study in detail the nets with diagonal receptive eld matrices. Parameters of the networks are learned by a simple procedure. Convergence and the rates of convergence of RRBF nets in the mean integrated absolute error (MIAE) sense are studied under mild conditions imposed on some of the network parameters. Obtained results give also upper bounds on the performance of RRBF nets learned by minimizing empirical L1 error.

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تاریخ انتشار 1997