Page 68 - profile2014.indd
P. 68
研究員
呂俊賢 Chun-Shien Lu
Research Fellow
Ph.D., Electrical Engineering, National Cheng-Kung University
Tel: +886-2-2788-3799 ext. 1513 Fax: +886-2-2782-4814
Email: lcs@iis.sinica.edu.tw
http://www.iis.sinica.edu.tw/~lcs
● Research Fellow, Institute of Research Description
Information Science, Academia
Sinica, Taiwan, ROC (2013/3–pre-
sent) My recent research interests mainly focus on algorithm design, theoretic analysis, and applica-
● Associate Research Fellow, tions of Compressive Sensing (CS). CS is a revolutionary methodology of simultaneously sensing
Institute of Information Sci- and compressing signals, and builds a new sampling theorem beyond the Nyquist rate. We are
ence, Academia Sinica, Taiwan currently interested in fundamental issues of optimal sensing matrix design, fast and accurate
(2006/7–2013/3) sparse signal recovery algorithms, dictionary learning, and theoretical but more practical bounds
● Adjunct Associate Professor, De- for sparse signal recovery.
partment of CSI, National Taipei For optimal sensing matrix design, conventional approaches are mostly based on reducing mu-
University of Technology, Taiwan
(2006/9–2008/1) tual coherence between a pair of sensing matrix and sparsifying basis. This seems to be intui-
tive and reasonable but the resultant optimal sensing matrix does not necessarily lead to good
● Associate Editor, IEEE sparse signal recovery performance. We will investigate this topic by exploring and comparing
Trans. on Image Processing the existing criteria.
(2010/12~2014/12)
● Ta-You Wu Memorial Award, For sparse signal recovery, many algorithms have been proposed. However, we nd that the the-
National Science Council, Taiwan, oretic recovery bound and practical performance are still not consistent. In fact, it is very often
ROC (2007) that the theoretical bounds are too strict to t practical situations. Our goal is to close the gap
between them.
Our representative results on compressive sensing are summarized as follows:
(1) We have proposed a sparse Fast Fourier Transform (sFFT) method that is faster than MIT’s methods (also known as state-of-the-art) with bet-
ter reconstructed results. The advantage also includes the easy selection of parameters and easy implementation for sFFT without needing
to know sparsity of a signal.
(2) We have developed a compressed sensing detector design for space shift keying for MIMO systems, a compressed sensing-based clone iden-
ti cation method for sensor networks, and compressed sensing-based cooperative spectrum sensing for cognitive radio networks.
(3) We have presented a distributed compressive video sensing (DCVS) method to simultaneously sense and compress videos.
Publications
1. Tsung-Hsun Chien, Wei-Jie, Liang, and Chun-Shien Lu, ``A Sparse Representation for Image Similarity Assessment,’’
Practical Subspace Multiple Measurement Vectors Algorithm IEEE Trans. on Multimedia, Vol. 13, No. 5, pp. 1019-1030,
for Cooperative Spectrum Sensing,’’ Proc. IEEE Globecom, 2011.
Austin, TX, 2014.
7. Chao-Yung Hsu, Chun-Shien Lu, and Soo-Chang Pei, ``Tem-
2. Yao-Tung Tsou, Chun-Shien Lu, and Sy-Yen Kuo, “MoteSec- poral Frequency of Flickering-Distortion Optimized Video
Aware: A Practical Secure Mechanism for Wireless Sensor Halftoning for Electronic Paper,’’ IEEE Trans. on Image Pro-
Networks,’’ IEEE Trans. on Wireless Communications, vol. cessing, Vol. 20, No. 9, pp. 2502-2514, 2011.
12, no. 6, pp. 2817-2829, 2013.
8. Chia-Mu Yu, Yao-Tung Tsou, Chun-Shien Lu, and Sy-Yen
3. Chia-Mu Yu, Yao-Tung Tsou, Chun-Shien Lu, and Sy-Yen Kuo, “Practical and Secure Multidimensional Queries in
Kuo, “Localized Algorithms for Detection of Node Replica- Tiered Sensor Networks,’’ IEEE Trans. on Information Foren-
tion Attacks in Mobile Sensor Networks,’’ IEEE Trans. on In- sics and Security, vol. 6, no. 2, pp. 241-255, 2011.
formation Forensics, and Security, Vol. 8, No. 5, pp. 754-768,
2013. 9. Chia-Mu Yu, Yao-Tung Tsou, Chun-Shien Lu, and Sy-Yen
Kuo, “Constrained Function based Message Authentication
4. Chao-Yung Hsu, Chun-Shien Lu, and Soo-Chang Pei, ``Im- for Sensor Networks,’’ IEEE Trans. on Information Forensics
age Feature Extraction in Encrypted Domain with Privacy- and Security, vol. 6, no. 2, pp. 407-425, 2011.
Preserving SIFT,’’ IEEE Trans. on Image Processing, Vol. 21,
No. 11, pp. 4593-4607, 2012. 10. Chia-Mu Yu, Chun-Shien Lu, and Sy-Yen Kuo, “Non-Interac-
tive Pairwise Key Establishment for Sensor Networks,’’ IEEE
5. Chun-Shien Lu and Chao-Yung Hsu, ``Constraint-Optimized Trans. on Information Forensics and Security, Vol. 5, No. 3,
Keypoint Removal/Insertion Attack: Security Threat to Scale- pp. 556-569, 2010.
Space Image Feature Extraction,’’ ACM Multimedia Confer- 11. Chia-Mu Yu, Chun-Shien Lu, and Sy-Yen Kuo, “A Simple
ence (ACM MM), Oct. 30-Nov. 02, Nara, Japan, pp. 629-638, Non-Interactive Pairwise Key Establishment Scheme in Sen-
2012. (full paper, acceptance rate 20.2%)
th
sor Networks,’’ Proc. The 6 IEEE Communications Society
6. Li-Wei Kang, Chao-Yung Hsu, Hung-Wei Chen, Chun-Shien Conference on Sensor, Mesh and Ad Hoc Communications
Lu, Chih-Yang Lin, and Soo-Chang Pei, ``Feature-based and Networks (SECON), June 22-26, 2009. (acceptance rate
18.5%)
68 研究人員 Research Faculty
