本文汇总了信号处理领域的核心研究方向和技术，包括压缩感知、小波变换、多尺度分析等。涉及多位专家的研究成果及应用案例，如Donoho的信号去噪研究、Candes在压缩感知方面的贡献等。
http://home.ustc.edu.cn/~roy/Relation.html
SR+相关研究+From http://home.ustc.edu.cn/~roy/Relation.html
☆ D. Donoho, Statistical Applications, Signal Denoising, Curvelets, Ridgelets.
☆ S. Mallat, Image Compression, Matching Pursuit, Wavelet, Texture Gradient, Bandelets.
☆ M. Vetterli, Multirate Signal Processing, Computational Complexity.
☆ M. N. Do, Multirate Signal Processing, Contourlet.
☆ R. Baraniuk, Sparse Signal Processing, Compressed Sensing and Machine Learning.
☆ J. Romberg, Compressed Sensing, Image Processing and Multiscale Analysis.
☆ E. Candes, Compressed Sensing, Curvelet and Ridgelet.
☆ Compressed Sensing, http://dsp.rice.edu/cs.
☆ Wavelet Tool Box, http://taco.poly.edu/WaveletSoftware/index.html.
☆ M. Elad , Signal and Image Processing, Numerical Analysis and Machine Learning.
☆ X. L. Wu , Image Processing, Image Coding.
☆ J. E. Fowler, Data Compression and Image Processing, Hyperspectral Image Coding.
☆ E. Magli, Vedio Coding, Remote Sensing Image Compression and Distributed Source Coding.
☆ X. B. Qu, Medical Image Reconstruction, Compressed Sensing and Multiscale Transform.
☆ Y. M. Lu , Signal Processing, Sparse Sampling and Sparse Representation Theory, Inverse Problem.
☆ G. Peyre , Bandelet, Signal Processing.
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