研究領域
1、自適應信號處理；
2、雷達成像與後處理技術；
3、陣列信號處理；
4、智慧型信息處理（現主要從事從結構和功能上仿大腦信息處理）；
5、新體制雷達信號處理；
科研項目
主要科研項目：
1、主持項國家自然科學基金1項；
2、主持國防預研基金2項；
3、主持橫向課題1項；
4、參加重要項目3項。
教學情況
《現代信號處理》(碩士生和博士生課程)；
《盲信號處理》》(碩士生課程)。
研究成果
他發表的有代性表論文(與SCI檢索有關的論文)如下：
[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 , 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.
