In this article, we consider the binary partitioned approach with pattern index information, propose an neural network array (NNA) that performs the pattern recognition task by combining the binary partitioned approach with decision trees, and verify that the NNA can not only reduce the computation cost of training and recognition but also reduce the classification error rate. Speaker identification with the radial basis function neural network array (RBFNNA) is discussed in detail as an application of the NNA.
Yue, X., Ye, D., Zheng, C., & Wu, X. (2002). Neural networks for improved text-independent speaker identification. IEEE Engineering in Medicine and Biology Magazine, 21(2), 53-58. https://doi.org/10.1109/MEMB.2002.1000186