Approximation by fully complex multilayer perceptrons

Neural Computation

Volumn 15, Issue 7, 2003, Pages 1641-1666

  Kim, Taehwan ^a   Adali, Tülay ^b  

^a MITRE CORPORATION   (United States)

^b University of Marylandw Baltimore County   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; ARTIFICIAL NEURAL NETWORK;

NEURAL NETWORKS (COMPUTER);

EID: 0038159963     PISSN: 08997667     EISSN: None     Source Type: Journal    
DOI: 10.1162/089976603321891846     Document Type: Article

References (33)

1. Ash, B. R. (1972). Real analysis and probability. New York: Academic Press.
2. Benvenuto, N., Marchesi, M., Piazza, F., & Uncini, A. (1991). Non linear satellite radio links equalized using blind neural networks. In Proc. of International Conference on Acoustics Speech and Signal Processing (Vol. 3, pp. 1521-1524). Piscataway, NJ: IEEE Press.
3. Benvenuto, N., & Piazza, F. (1992). On the complex backpropagation algorithm. IEEE Trans. on Signal Processing, 40, 967-969.
4. Bishop, C. (1999). Neural networks for pattern recognition. New York: Oxford University Press.
5. Chen, S., Grant, P. M., McLaughlin, S., & Mulgrew, B. (1993). Complex-valued radial basis function networks. In Proc. of Third IEEE International Conference on Artificial Neural Networks (pp. 148-152). Piscataway, NJ: IEEE Press.
6. Churchill, R., & Brown, J. (1992). Complex variables and applications (5th ed.). Seoul, Korea: McGraw-Hill.
7. Clarke, T. (1990). Generalization of neural network to the complex plane. In Proc. of International Joint Conference on Neural Networks (Vol. 2, pp. 435-440).
8. Cybenko, G. (1989). Approximation by superpositions of a sigmoidal function, Mathematics of Control, Signals, and Systems, 2, 303-314.
9. Deng, J., Sundararajan, N., & Saratchandran, P. (2000). Communication channel equalization using complex-valued minimal radial basis functions neural network. In Proc. of IEEE IJCNN 2000 (Vol. 5, pp. 372-377). Piscataway, NJ: IEEE Press.
10. Funahashi, K. (1989). On the approximate realization of continuous mappings by neural networks. Neural Networks, 2, 183-192.
11. Georgiou, G., & Koutsougeras, C. (1992). Complex backpropagation. IEEE Trans. on Circuits and Systems II, 39, 330-334.
12. Haykin, S. (1999). Neural networks: A comprehensive foundation (2nd ed.). New York: Macmillan.
13. Hirose, A. (1992). Continuous complex-valued back-propagation learning. Electronics Letters, 28, 1854-1855.
14. Hornik, K., Stinchcombe, M., & White, H. (1989). Multilayer feedforward networks are universal approximators. Neural Networks, 2, 359-366.
15. Ibnkahla, M., & Castanie, F. (1995). Vector neural networks for digital satellite communications. In Proc. of International Conference on Communications (Vol. 3, pp. 1865-1869). Piscataway, NJ: IEEE Press.
16. Katz, A. (2001, December). Linearization: Reducing distortion in power amplifiers. IEEE Microwave Magazine, December, 37-49.
17. Kechriotis, G., & Manolakos, E. (1994). Training fully recurrent neural networks with complex weights. IEEE Trans. on Circuits and Systems - II: Analog and Digital Signal Processing, 41, 235-238.
18. Kim, T. (2002). Fully complex multilayer perceptron and its application to communications. Unpublished doctoral dissertation, University of Maryland.
19. Kim, T., & Adali, T. (2000). Fully complex backpropagation for constant envelop signal processing. In Proc. of IEEE Workshop on Neural Networks for Signal Processing (NNSP) (pp. 231-240). Piscataway, NJ: IEEE Press.
20. Kim, T., & Adali, T. (2001). Complex backpropagation neural network using elementary transcendental activation functions. In Proc. of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) (Vol. 2). Piscataway, NJ: IEEE Press.
21. Kim, T., & Adali, T. (2002). Fully-complex multilayer perceptron for nonlinear signal processing. Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology, 32, 29-43.
22. Kim, T., & Hegarty, C. (2002). Simulated nonlinear prediction and cancellation of ionospheric scintillation in GPS/WAAS software receivers. In Ionospheric Effects Symposium 2002(IES2002) (pp. 5B9-1-5B9-12). Alexandria, VA: JMG Associates.
23. Langlet, F., Abdulkader, H., Roviras, D., Mallet, A., & Castanie, F. (2001). Adaptive predistortion for solid state power amplifier using multi-layer perceptron. In IEEE Globecom'01 (Vol. 1, pp. 325-329). Piscataway, NJ: IEEE Press.
24. Leung, H., & Haykin, S. (1991). The complex backpropagation algorithm. IEEE Trans. on Signal Proc., 3, 2101-2104.
25. Mandic, D., & Chambers, J. (2001). Recurrent neural networks for prediction. New York: Wiley.
26. Needham, T. (2000). Visual complex analysis. New York: Oxford University Press.
27. Park, D-C., & Jeong, T-K. (2002). Complex-bilinear recurrent neural network for equalization of a digital satellite channel. IEEE Trans. on Neural Networks, 13, 722-725.
28. Riedmiller, M., & Braun, H. (1993). A direct adaptive method for faster back-propagation learning: The RPROP algorithm. In Proc. of IEEE International Conference on Neural Network, 1, 586-591. Piscataway, NJ: IEEE Press.
29. Rudin, W. (1974). Real and complex analysis (2nd ed.). New York: McGraw-Hill.
30. Rudin, W. (1991). Functional analysis (2nd ed.). New York: McGraw-Hill.
31. Silverman, H. (1975). Complex variables. Boston: Houghton Mifflin.
32. Uncini, A., Vecci, L., Campolucci, P., & Piazza, F. (1999). Complex-valued neural networks with adaptive spline activation functions. IEEE Trans. on Signal Processing, 47, 505-514.
33. You, C., & Hong, D. (1998). Nonlinear blind equalization schemes using complex-valued multilayer feedforward neural networks. IEEE Trans. on Neural Networks, 9, 1442-1455.