Center for Teaching and Learning Development

Organization profile

Organisation profile

To promote and support exemplary teaching, NCKU established the Center for Teaching and Learning Development on Dec. 22, 2010. The Center’s mission is to enhance NCKU’s overall teaching quality by integrating teaching resources. The Center is committed to enhance the quality of education by providing teachers with resources, programs and support that promote excellence in teaching, it also seeks to create an innovative learning environment for teachers and students by hosting workshops, providing consultations, promoting digital teaching, and conducting research on curriculum reform.

Fingerprint Dive into the research topics where Center for Teaching and Learning Development is active. These topic labels come from the works of this organisation's members. Together they form a unique fingerprint.

Convex optimization Engineering & Materials Science
measurement algorithm Social Sciences
Recovery Engineering & Materials Science
Compressed sensing Engineering & Materials Science
Tensors Engineering & Materials Science
Costs Engineering & Materials Science
Computational complexity Engineering & Materials Science
Mathematical operators Engineering & Materials Science

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Research Output 2014 2017

  • 5 Conference contribution
  • 2 Article

Distributed Compressive Sensing: Performance analysis with diverse signal ensembles

Hsieh, S. H., Liang, W-J., Lu, C. S. & Pei, S. C., 2017 Oct 23, 25th European Signal Processing Conference, EUSIPCO 2017. Institute of Electrical and Electronics Engineers Inc., p. 1324-1328 5 p. 8081423. (25th European Signal Processing Conference, EUSIPCO 2017; vol. 2017-January).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Theoretical stopping criteria guided Greedy Algorithm for Compressive Cooperative Spectrum Sensing

Liang, W. J., Chien, T. H. & Lu, C. S., 2017 Oct 1, In : Computer Communications. 111, p. 165-175 11 p.

Research output: Contribution to journalArticle

Compressed sensing
Cognitive radio
Recovery
4 Citations (Scopus)

Tree structure sparsity pattern guided convex optimization for compressive sensing of large-scale images

Liang, W-J., Lin, G. X. & Lu, C. S., 2017 Feb 1, In : IEEE Transactions on Image Processing. 26, 2, p. 847-859 13 p., 7762896.

Research output: Contribution to journalArticle

Convex optimization
Mathematical operators
Costs