Nonlinear adaptive prediction of speech with a pipelined recurrent neural network

@article{Baltersee1998NonlinearAP,
  title={Nonlinear adaptive prediction of speech with a pipelined recurrent neural network},
  author={Jens Baltersee and Jonathon A. Chambers},
  journal={IEEE Trans. Signal Processing},
  year={1998},
  volume={46},
  pages={2207-2216}
}
New learning algorithms for an adaptive nonlinear forward predictor that is based on a pipelined recurrent neural network (PRNN) are presented. A computationally efficient gradient descent (GD) learning algorithm, together with a novel extended recursive least squares (ERLS) learning algorithm, are proposed. Simulation studies based on three speech signals that have been made public and are available on the World Wide Web (WWW) are used to test the nonlinear predictor. The gradient descent… CONTINUE READING
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References

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Showing 1-6 of 6 references

Adaptive Filter Theory,3rd ed

S. Haykin
Englewood Cliffs, NJ: Prentice-Hall, • 1996

Adaptive IIR filtering

IEEE ASSP Magazine • 1989

Fundamentals of Statistical Signal Processing: Estimation Theory

S. M. Kay
Englewood Cliffs, NJ: Prentice-Hall, • 1989

Linear prediction: A tutorial review

Proceedings of the IEEE • 1975

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