Abstract
To solve the training problems for complex problems, a new learning algorithm based on continued fractional weight function for training neural networks is proposed, which is different from that of polynomial weight functions. The continued fractional weight functions using interpolation methods are more suitable for training the patterns obtained by some rational problems. The analysis of generalization is also presented in this paper. At last, to illustrate the power of the new learning algorithm, a simulation example is presented to show that the new algorithm proposed in this paper has good performance both on generalization and calculating precision.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.