%0 Journal Article %A Hazem M. El-Bakry and Qiangfu Zhao %D 2008 %J International Journal of Computer and Information Engineering %B World Academy of Science, Engineering and Technology %I Open Science Index 17, 2008 %T Fast Complex Valued Time Delay Neural Networks %U https://publications.waset.org/pdf/3218 %V 17 %X Here, a new idea to speed up the operation of complex valued time delay neural networks is presented. The whole data are collected together in a long vector and then tested as a one input pattern. The proposed fast complex valued time delay neural networks uses cross correlation in the frequency domain between the tested data and the input weights of neural networks. It is proved mathematically that the number of computation steps required for the presented fast complex valued time delay neural networks is less than that needed by classical time delay neural networks. Simulation results using MATLAB confirm the theoretical computations. %P 1640 - 1650