Determining initial weights of feedforward neural networks based on least squares method
β Scribed by Y. F. Yam; T. W. S. Chow
- Publisher
- Springer US
- Year
- 1995
- Tongue
- English
- Weight
- 366 KB
- Volume
- 2
- Category
- Article
- ISSN
- 1370-4621
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
We present the theoretical results about the construction of confidence intervals for a nonlinear regression based on least squares estimation and using the linear Taylor expansion of the nonlinear model output. We stress the assumptions on which these results are based, in order to derive an approp
An algorithm based on the Marquardt-Levenberg leastsquares optimization method has been shown by \(S\). Kollias and D. Anastasiou to be a much more efficient training method than gradient descent, when applied to some small feedforward neural networks. Yet, for many applications, the increase in com