Abstract
This paper presents the use of self-organized neural network inspired by the immune algorithm for the prediction of speech signal. Two speech signals are utilized, woman and man voices counting from one to ten in Arabic. The simulation results were compared with the multilayer perceptrons neural network. A new training algorithm was used with the self-organised multilayer perceptrons neural network that is inspired by the immune using weight decay. The simulation results indicated slight improvement of the use of regularisation technique for the multilayer perceptrons and no improvement when using the self-organized neural network inspired by the immune algorithm for the two speech signals.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Kim, S.-S.: Time-delay recurrent neural network for temporal correlations and prediction. Neurocomputing 20(1–3), 253–263 (1998)
Lawrence, S., Giles, C.L.: Overfitting and neural networks: conjugate gradient and backpropagation. In: International Joint Conference on Neural Network, pp 114–119. IEEE Computer Society, Italy, CA (2000)
Widyanto, M.R., Nobuhara, H., Kawamoto, K., Hirota, K., Kusumoputro, B.: Improving recognition and generalization capability of back-propagation NN using self-organized network inspired by immune algorithm. Appl. Soft Comput. 6, 72–84 (2005)
Hanson, S.J., Pratt, L.: A comparison of different biases for minimal network construction with back-propagation. Advances in Neural Information Processing Systems II, pp. 177–185. Morgan Kaufmann, Los Altos (1990)
Weigend, A.S., Rumelhart, D.E., Huberman, B.A.: Generalization by weight elimination with application to forecasting. In: Lippmann, R.P., Moody, J.E., Touretzky, D.S. (eds.) Advances in Neural Information Processing Systems III, pp. 875–882. Morgan Kaufmann, Los Altos (1991)
Kaita, T., Tomita, S., Yamanaka, J.: On a HONN for distortion invariant pattern recognition. Pattern Recogn. Lett. 23, 977–984 (2002)
Chen, A.S., Leung, M.T.: Regression neural network for error correction in foreign exchange forecasting and trading. Comput. Oper. Res. 31, 1049–1068 (2004)
Gupta, A., Lam, S.M.: Weight decay backpropagation for noisy data. Neural Netw. 11(6), 1127–1137 (1998)
Haykin, S., Lee, L.: Nonlinear adaptive prediction of nonstationary signals. IEEE Trans. Signal Process. 43(2), 526–535 (1995)
Giles, C.L., Maxwell, T.: Learning, invariance and generalisation in high-order neural networks. Appl. Optics 26(23), 4972–4978 (1987). Optical Society of America, Washington DC
Giles, C.L., Bollacker, K., Lawrence, S.: CiteSeer: an automatic citation indexing system. In: Proceedings of the 3rd ACM Conference on Digital Libraries (DL 1998), pp. 89–98. ACM, New York (1998)
Durbin, R., Rumelhart, D.E.: Product units: a computationally powerful and biologically plausible extension to back-propagation networks. Neural Comput. 1, 133–142 (1989)
Mirea, L., Marcu, T.: System identification using functional-link NN with dynamic structure. In: 15th Triennial World Congress, Barcelona, Spain (2002)
Fei, G., Yu, Y.L.: A modified sigma-Pi BP network with self-feedback and its application in time series analysis. In: Proceedings of the 5th International Conference, vol. 2243–508F, pp. 508–515 (1994)
Cass, R., Radl, B.: Adaptive process optimisation using functional-link networks and evolutionary algorithm. Control Eng. Pract. 4(11), 1579–1584 (1996)
Timmis, J.I.: Ariticial immune systems: a novel data analysis technique inspired by the immune network theory. University of Wales (2001)
Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification. Wiley, Canada (2001)
Bishop, C.M.: Neural Networks for Pattern Recognition. Oxford University Press, Cambridge (1995)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Al-Jumeily, D., Hussain, A.J., Fergus, P., Radi, N. (2015). Self-organized Neural Network Inspired by the Immune Algorithm for the Prediction of Speech Signals. In: Huang, DS., Jo, KH., Hussain, A. (eds) Intelligent Computing Theories and Methodologies. ICIC 2015. Lecture Notes in Computer Science(), vol 9226. Springer, Cham. https://doi.org/10.1007/978-3-319-22186-1_65
Download citation
DOI: https://doi.org/10.1007/978-3-319-22186-1_65
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-22185-4
Online ISBN: 978-3-319-22186-1
eBook Packages: Computer ScienceComputer Science (R0)