@inproceedings{04dc97c733c44e66939c605972010179,
title = "A New Modified Hybrid Learning Algorithm for Feedforward Neural Networks",
abstract = "In this paper, a new modified hybrid learning algorithm for feedforward neural networks is proposed to obtain better generalization performance. For the sake of penalizing both the input-to-output mapping sensitivity and the high frequency components in training data, the first additional cost term and the second one are selected based on the first-order derivatives of the neural activation at the hidden layers and the second-order derivatives of the neural activation at the output layer, respectively. Finally, theoretical justifications and simulation results are given to verify the efficiency and effectiveness of our proposed learning algorithm.",
keywords = "Hide Layer, Output Layer, Feedforward Neural Network, High Frequency Component, Modify Algorithm",
author = "Fei Han and Deshuang Huang and Cheung, {Yiu Ming} and Guangbin Huang",
note = "Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; Second International Symposium on Neural Networks: Advances in Neural Networks - ISNN 2005 ; Conference date: 30-05-2005 Through 01-06-2005",
year = "2005",
month = may,
day = "2",
doi = "10.1007/11427391_91",
language = "English",
isbn = "9783540259121",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "572--577",
editor = "Jun Wang and Xiaofeng Liao and Zhang Yi",
booktitle = "Advances in Neural Networks - ISNN 2005",
edition = "1st",
url = "https://link.springer.com/book/10.1007/b136476",
}