Computational Oriented Real-time Convex Optimization in Signal Processing

Project Details

Description

Convex optimization is an important tool in many areas of engineering. Recently we have seen convex optimization being used in an on-line setting where computational power and time is limited. In this case the optimization algorithm can usually only be obtained as a handtailored solution by convex optimization experts. This project will bring forth algorithms and software that automate this process such that a greater range of engineers and scientists can easily use real-time convex optimization. The proposed algorithms will, compared to state-of-the-art, efficiently use the possibilities of modern parallel and embedded computing platforms. This unleashes convex optimization models developed in the last 15 years for use in real-time signal processing systems.
AcronymRTC
StatusFinished
Effective start/end date01/06/201430/06/2017

Funding

  • The Danish Council for Independent Research| Technology and Production Sciences
  • Independent Research Fund Denmark | Sapere Aude

Fingerprint Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.

  • Research Output

    • 10 Article in proceeding
    • 6 Journal article
    • 1 Report

    A Fast Interior-Point Method for Atomic Norm Soft Thresholding

    Hansen, T. L. & Jensen, T., Dec 2019, In : Signal Processing. 165, p. 7-19 13 p.

    Research output: Contribution to journalJournal articleResearchpeer-review

  • 20 Downloads (Pure)

    Speech Dereverberation Based on Convex Optimization Algorithms for Group Sparse Linear Prediction

    Giacobello, D. & Jensen, T. L., 2018, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018. IEEE, p. 446-450 5 p. 8462560. (I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings).

    Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

    File
    6 Citations (Scopus)
    206 Downloads (Pure)

    A Fast Algorithm for Maximum Likelihood Estimation of Harmonic Chirp Parameters

    Jensen, T. L., Nielsen, J. K., Jensen, J. R., Christensen, M. G. & Jensen, S. H., 2017, In : I E E E Transactions on Signal Processing. 65, 19, p. 5137 - 5152

    Research output: Contribution to journalJournal articleResearchpeer-review

    File
  • 8 Citations (Scopus)
    472 Downloads (Pure)