1.    Zhu R X, Bao J L, Yuan H X. A fast algorithm for OFDM power amplifier linearization. Signal Processing, 2012, 28(1): 1602-1606 (in Chinese)

  2.    Bertran E, O’Droma M S, Gilabert P L,et al.Performance analysis of power amplifier back-off levels in UWB transmitters. IEEE Transactions on Consumer Electronics, 2007, 53(4): 1309-1313

  3.    Chang L C, Lan Y L. Analysis of amplitude and phase predistortion and polynomial-based predistortion in OFDM systems. Proceedings of the 6th International Conference on Information, Communications & Signal Processing (ICICS’07), Dec 10-13, 2007, Singapore. Piscataway, NJ, USA: IEEE, 2007: 5p

  4.    Chen B, Ren G C, Gong Y P. Study on pre-distortion technique based on polynomial and look-up table. China Information Security, 2011 (3): 44-46 (in Chinese)

  5.    Zhai J F, Xie N D, Zhou J Y, et al. A novel adaptive baseband digital predistortion technique. International Journal of Microwave and Optical Technology, 2007, 2(2): 119-123

  6.    Garcia-Ducar P, De Mingo J, Valdovinos A. Predistortion method for nonlinear distortion cancellation in WiMAX transmitters. Proceedings of the 3rd International Symposium on Wireless Communication Systems (ISWCS’06), Sep 6-8, 2006, Valencia, Spain. Piscatawaw, NJ, USA: IEEE, 2006: 786-790

  7.    Filippov T V, Sahu A, Kirichenko A F, et al. Look-up table for superconductor digital-RF predistorter. IEEE Transactions on Applied Superconductivity, 2007, 17(2): 561-564

  8.    Wang H P, Cao G H, Xu H J, et al. Application of neural network on distortion correction based of standard grid. Proceeding of the 2009 IEEE International Conference on Mechatronics and Automation (ICMA’09), Aug 9-12, 2009, Changchun, China. Piscataway, NJ, USA: IEEE, 2009: 2717-2722

  9.    Mkadem F, Boumaiza S. Physically inspired neural network model for RF amplifier behavioral modeling and digital predistortion. IEEE Transactions on Microwave Theory and Techniques, 2011, 59(4): 913-923

10.    Lee K C, Gardner P. A novel digital predistorter technique using an adaptive neuro-fuzzy inference system. IEEE Communications Letters, 2003, 7(2): 55-57

11.    Lee K C, Gardner P. Adaptive neuro-fuzzy inference system (ANFIS) digital predistorter for RF power amplifier linearization. IEEE Transactions on Vehicular Technology, 2006, 55(1): 43-51

12.    Zhai J F, Zhou J Y, Zhang L, et al. ANFIS implementation in FPGA for power amplifier linearization with digital predistortion. Proceedings of the International Conference on Microwave and Millimeter Wave Technology (ICMMT’08), Apr 21-24, 2008, Nanjing, China. Piscataway, NJ, USA: IEEE, 2008: 1474-1476

13.    Saleh A A M. Frequency-independent and frequency-dependent nonlinear models of TWT amplifiers. IEEE Transactions on Communications, 1981, 29(11): 1715-1720

14.    Zhang Y, Zhou C G. Taste identification of tea through a fuzzy neural network based on fuzzy c-means clustering. The Journal of China Universities of Posts and Telecommunications, 2003,10(3): 55-61

15.    Zhao Q, Li G J, Xing S X. FCM algorithm based on the optimization parameters of objective function point. Proceedings of the 2010 International Conference on Computing, Control and Industrial Engineering (CCIE’10): Vol 2, Jun 5-6, 2010, Wuhan, China. Piscataway, NJ, USA: IEEE, 2010: 331-333