Complex-valued forecasting of wind profile

@inproceedings{Goh2006ComplexvaluedFO,
  title={Complex-valued forecasting of wind profile},
  author={Su Lee Goh and Mo Chen and Darko Popovic and Kazuyuki Aihara and Dragan Obradovic and Danilo P. Mandic},
  year={2006}
}
This paper presents a novel approach for the simultaneous modelling and forecasting of wind signal components. This is achieved in the complex domain by using novel neural network algorithms and architectures. We first perform a signal nonlinearity and component-dependent analyses, which suggest the use of modular complex-valued recurrent neural networks (RNNs). This RNN-based modelling rests upon a combination of nonlinearity, complexity and internal memory and allows for the multiple step… CONTINUE READING

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