References
- Bracewell R. (1999). The Fourier Transform and Its Applications, 3rd Edn., McGraw-Hill, New York, NY.
- Chu E. and George A. (2000). Inside the FFT Black Box: Serial and Parallel Fast Fourier Transform Algorithms, CRC Press, Boca Raton, FL.
- Dutt A. and Rokhlin V. (1993). Fast Fourier transforms for nonequispaced data, Journal of Scientific Computing14(6): 1368-1393.
- Gonzalez R. C. and Woods R. E. (1999). Digital Image Processing, 2nd Edn., Prentice-Hall, Inc., Boston, MA.
- Halawa K. (2008). Fast method for computing outputs of Fourier neutral networks, in: K. Malinowski and L. Rutkowski, Eds., Control and Automation: Current Problems and Their Solutions, EXIT, Warsaw, pp. 652-659, (in Polish).
- Hyvarinen A. and Oja E. (2000). Independent component analysis: Algorithms and applications, Neural Networks13(4): 411-430.
- Joliffe I. T. (1986). Principal Component Analysis, Springer-Verlag, New York, NY.
- Kegl B., Krzyżak A., Linder T. and Zeger K. (2000). Learning and design of principal curves, IEEE Transactions on Pattern Analysis and Machine Intelligence22(13): 281-297.
- Li H. and Sun Y. (2005). The study and test of ICA algorithms, Proceedings of the International Conference on Wireless Communications, Networking and Mobile Computing, Wuhan, China, pp. 602-605.
- Liu Q. H. and Nyguen N. (1998). An accurate algorithm for nonuniform fast Fourier transforms, Microwave and Guided Wave Letters8(1): 18-20.
- Nelles O. (2001). Nonlinear System Identification: From Classical Approaches to Neural Network and Fuzzy Models, Springer-Verlag, Berlin.
- Rafajłowicz E. and Pawlak M. (1997). On function recovery by neural networks based on orthogonal expansions, Nonlinear Analysis, Theory and Applications30(3): 1343-1354.
- Rafajłowicz E. and Skubalska-Rafajłowicz E. (1993). FFT in calculating nonparametric regression estimate based on trigonometric series, International Journal of Applied Mathematics and Computer Science3(4): 713-720.
- Sher C. F., Tseng C. S. and Chen C. (2001). Properties and performance of orthogonal neural network in function approximation, International Journal of Intelligent Systems16(12): 1377-1392.
- Tseng C. S. and Chen C. S. (2004). Performance comparison between the training method and the numerical method of the orthogonal neural network in function approximation, International Journal of Intelligent Systems19(12): 1257-1275.
- Van Loan C. (1992). Computational Frameworks for the Fast Fourier Transform, SIAM, Philadelphia, PA.
- Walker J. (1996). Fast Fourier Transforms, CRC Press, Boca Raton, FL.
- Zhu C., Shukla D. and Paul F. (2002). Orthogonal functions for system identification and control, in: C. T. Leondes (Ed.), Neural Networks Systems, Techniques and Apllications: Control and Dynamic Systems, Academic Press, San Diego, CA, pp. 1-73.