【人物简介】

　　冯大政, 男, 1959年12月生, 工学博士, 教授, 博士导师. 中国电子学会高级会员, 美国IEEE 学会会员. 他长期从事信号与信息处理研究, 发表期刊学术论文九十多篇，其中国际期刊论文三十多篇，IEEE会刊论文十多篇。他获得过教育部跨世纪人才基金， 获得省部级科技进步二等奖三项. 在信号处理领域, 他已经有一定国际知名度.近年来，在自适应信号处理，盲信号处理，机载雷达信号处理，MIMO雷达信号处理和InSAR等研究达到国际先进水平。

【研究方向】

1.信号参数估计 2.仿大脑信息处理:场景感知、模式识别等 3.雷达信号处理

【研究成果】

近年来，冯大政教授在自适应信号处理、盲信号处理、机载雷达信号处理、MIMO雷达信号处理和InSAR等研究方面达到了国际先进水平，在信号处理这一领域，享有一定的知名度。曾荣获教育部跨世纪人才基金、省部级科技进步二等奖3项。

【科研项目】

　　1、主持项国家自然科学基金1项。 　　2、主持973子课题1项。 　　3、主持横向课题1项。 　　4、主持重要项目1项。 　　5、参加重要项目3项。

【论文著作】

　　[1] Da-Zheng Feng et al., “Fast approximate inverse-power iteration algorithm for adaptive FIR filtering,” IEEE Trans. Signal Processing, No. 10, pp. 4032-4039, 2006. 　　[2] Nan Wu, and Da-Zheng Feng, “A locally adaptive filter of interferometric phase images,” IEEE Geoscience and Remote Sensing Letters, Vol. 3, No. 1, pp. 73-77, 2006. 　　[3] Yi Zhou, and Da-Zheng Feng, “A novel algorithm for two-dimensional frequency estimation,” Signal Processing, In Press, Corrected Proof, Available online (http://www.sciencedirect.com/science?), June 2006. 　　[4] Da-Zheng Feng, and Wei-Xing Zheng, “Fast RLS-type algorithm for unbiased equation-error adaptive IIR filtering based on approximate inverse-power iteration,” IEEE Trans. Signal Processing, No. 11, 2005. 　　[5] Da-Zheng Feng, Wei-Xing Zheng, and Ying Jia, “Neural network learning algorithms for tracking minor subspace in high dimensional data stream,” IEEE Trans. Neural Networks, No.3, 2005. 　　[6] Dong-Xia Chang, and Da-Zheng Feng et al., “A Fast recursive total least squares algorithm for adaptive IIR filtering,” IEEE Trans. Signal Processing, No. 3, 2005. 　　[7] Da-Zheng Feng, Xian-Da Zhang, and Zheng Bao, “A neural network learning for adaptively extracting cross-correlation features between two high dimensional data streams,” IEEE Trans. Neural Networks, Vol. 15, No. 6, pp. 1541-1554, Nov. 2004. 　　[8] Da-Zheng Feng et al., “A Fast recursive total least squares algorithm for adaptive FIR filtering,” IEEE Trans. Signal Processing, Vol. 52, No.10, pp. 2729-2737, Oct. 2004. 　　[9] Lei Huang, Shun-Jun Wu, Da-Zheng Feng, and Lin-Rang Zhang, “Low complexity method for signal subspace fitting,” Electronics Letters, Vol. 40, No. 14, pp. 847-848, July 2004. 　　[10] Da-Zheng Feng et al. “Neural network learning for principal component analysis: A multistage decomposition approach,” Chinese Journal of Electronics No. 1, Jan. 2004. 　　[11] Da-Zheng Feng, et al. “An efficient multistage decomposition approach for independent components,” Signal Processing, Vol. 83, pp. 181-197, Jan. 2003. 　　[12] Da-Zheng Feng, et al. “Multistage decomposition algorithm for blind source separation,” Progress in Natural Science, No. 5, May 2002. 　　[13] Da-Zheng Feng, et al. “A bi-iteration instrumental variable noise-subspace tracking algorithm,” Signal Processing, Vol. 81, pp. 2215-2221, 2001. 　　[14] Da-Zheng Feng, et al. “A cross-associative neural network for SVD of non-squared data matrix in signal processing,” IEEE Trans. Neural Networks, No. 5, pp. 1215-1221, Sept. 2001. 　　[15] Da-Zheng Feng, et al. “An extended recursive least-squares algorithm,” Signal Processing, Vol. 81, pp. 1075-1081, 2001. 　　[16] Da-Zheng Feng, et al. “A Cross-Associative Neural Network Used as SVD of Non-Square Data Matrix or Cross-correlation matrix in signal Processing,” Chinese Journal of Electronics No. 1, Jan. 2001. 　　[17] Da-Zheng Feng, et al., “Two-dimensional phase unwrapping based on the finite element method and FFT’s,” Chinese Journal of Electronics, No. 3, July 2000. 　　[18] Da-Zheng Feng, et al. “Modified RLS algorithm for unbiased estimation of FIR system with input and output noise,” IEE Electronics Letters, No. 3, pp. 273-274, Feb. 2000. 　　[19] Da-Zheng Feng, et al., “Total least mean squares algorithm,” IEEE Trans. Signal Processing, No. 8, pp. 2122-2130, Aug. 1998. 　　[20] Da-Zheng Feng, et al., “Cross-correlation neural network models for the smallest singular component of general matrix,” Signal Processing, Vol. 64, pp. 333-346, Feb. 1998. 　　[21] Da-Zheng Feng et al., “Modified Cross-Correlation neural networks,” Chinese Journal of Electronics, No. 2, May 1997.