TY - JFULL AU - Abiodun M. Aibinu and Momoh J. E. Salami and Amir A. Shafie and Athaur Rahman Najeeb PY - 2008/7/ TI - Increasing The Speed of Convergence of an Artificial Neural Network based ARMA Coefficients Determination Technique T2 - International Journal of Computer and Information Engineering SP - 1838 EP - 1845 VL - 2 SN - 1307-6892 UR - https://publications.waset.org/pdf/3015 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 18, 2008 N2 - In this paper, novel techniques in increasing the accuracy and speed of convergence of a Feed forward Back propagation Artificial Neural Network (FFBPNN) with polynomial activation function reported in literature is presented. These technique was subsequently used to determine the coefficients of Autoregressive Moving Average (ARMA) and Autoregressive (AR) system. The results obtained by introducing sequential and batch method of weight initialization, batch method of weight and coefficient update, adaptive momentum and learning rate technique gives more accurate result and significant reduction in convergence time when compared t the traditional method of back propagation algorithm, thereby making FFBPNN an appropriate technique for online ARMA coefficient determination. ER -