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Writing Your Own Training AlgorithmsIntroduction

7.10 Further Reading

The following are standard books on minimization:

J.E. Dennis and R.B. Schnabel (1983), Numerical Methods for Unconstrained Optimization and Nonlinear Equations, Prentice Hall, Englewood Cliffs, NJ.

R. Fletcher (1987), Practical Methods of Optimization, John Wiley & Sons, Chippenham, Great Britain.

Stopped search and the separable algorithms are explained in the following articles:

J. Sjöberg and L. Ljung (1995), Overtraining, Regularization, and Searching for Minimum with Application to Neural Nets, Int. J. Control, vol. 62, no. 6, pp. 1391-1407.

J. Sjöberg and M. Viberg (1997), Separable Non-linear Least-squares minimization—Possible Improvements for Neural Net Fitting, IEEE Workshop in Neural Networks for Signal Processing, Amelia Island Plantation, Florida, Sep. 24-26, pp. 345-354.

This standard book on neural networks may also be of interest:

S. Haykin (1999), Neural Networks: A Comprehensive Foundation, Second Edition, Macmillan, New York.

Writing Your Own Training AlgorithmsIntroduction

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