Abstract
This paper introduces a complex numbered version of the backpropagation algorithm, which can be applied to neural networks whose weights, threshold values, input and output signals are all complex numbers. This new algorithm can be used to learn complex numbered patterns in a natural way. We show that complex-BP can transform geometrical figures.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: 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.
