Imperial College London

DrWeiDai

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Senior Lecturer
 
 
 
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Contact

 

+44 (0)20 7594 6333wei.dai1 Website

 
 
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Location

 

811Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
to

52 results found

Ding W, Lu Y, Yang F, Dai W, Li P, Liu S, Song Jet al., 2016, Spectrally Efficient CSI Acquisition for Power Line Communications: A Bayesian Compressive Sensing Perspective, IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, Vol: 34, Pages: 2022-2032, ISSN: 0733-8716

JOURNAL ARTICLE

Dong J, Wang W, Dai W, Plumbley MD, Han Z-F, Chambers Jet al., 2016, Analysis SimCO Algorithms for Sparse Analysis Model Based Dictionary Learning, IEEE TRANSACTIONS ON SIGNAL PROCESSING, Vol: 64, Pages: 417-431, ISSN: 1053-587X

JOURNAL ARTICLE

Gao Z, Dai L, Dai W, Shim B, Wang Zet al., 2016, Structured Compressive Sensing-Based Spatio-Temporal Joint Channel Estimation for FDD Massive MIMO, IEEE TRANSACTIONS ON COMMUNICATIONS, Vol: 64, Pages: 601-617, ISSN: 0090-6778

JOURNAL ARTICLE

Ding W, Lu Y, Yang F, Dai W, Song Jet al., 2015, Sparse Channel State Information Acquisition for Power Line Communications, IEEE International Conference on Communications (ICC), Publisher: IEEE, Pages: 746-751, ISSN: 1550-3607

CONFERENCE PAPER

Ding W, Yang F, Dai W, Song Jet al., 2015, Time-Frequency Joint Sparse Channel Estimation for MIMO-OFDM Systems, IEEE COMMUNICATIONS LETTERS, Vol: 19, Pages: 58-61, ISSN: 1089-7798

JOURNAL ARTICLE

Gao X, Li X, Filos J, Dai Wet al., 2015, A Sequential Bayesian Algorithm for DOA Tracking in Time-Varying Environments, CHINESE JOURNAL OF ELECTRONICS, Vol: 24, Pages: 140-145, ISSN: 1022-4653

JOURNAL ARTICLE

Gao Z, Dai L, Dai W, Wang Zet al., 2015, Block Compressive Channel Estimation and Feedback for FDD Massive MIMO, 34th IEEE Conference on Computer Communications (INFOCOM), Publisher: IEEE, Pages: 49-50, ISSN: 2159-4228

CONFERENCE PAPER

Karseras E, Dai W, Dai L, Wang Zet al., 2015, Fast Variational Bayesian Learning for Channel Estimation with Prior Statistical Information, 16th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Publisher: IEEE, Pages: 470-474, ISSN: 2325-3789

CONFERENCE PAPER

Lu Y, Dai W, 2015, Improved AMP (IAMP) for Non-Ideal Measurement Matrices, 23rd European Signal Processing Conference (EUSIPCO), Publisher: IEEE, Pages: 1746-1750, ISSN: 2076-1465

CONFERENCE PAPER

Pitaval R-A, Dai W, Tirkkonen O, 2015, Convergence of Gradient Descent for Low-Rank Matrix Approximation, IEEE TRANSACTIONS ON INFORMATION THEORY, Vol: 61, Pages: 4451-4457, ISSN: 0018-9448

JOURNAL ARTICLE

Zhu X, Dai L, Dai W, Wang Z, Moonen Met al., 2015, Tracking A Dynamic Sparse Channel Via Differential Orthogonal Matching Pursuit, 34th IEEE Annual Military Communications Conference (MILCOM) on Leveraging Technology - The Joint Imperative, Publisher: IEEE, Pages: 792-797, ISSN: 2155-7578

CONFERENCE PAPER

Karseras E, Dai W, 2014, A FAST VARIATIONAL APPROACH FOR BAYESIAN COMPRESSIVE SENSING WITH INFORMATIVE PRIORS, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Publisher: IEEE, ISSN: 1520-6149

CONFERENCE PAPER

Zhao X, Dai W, 2014, Power Allocation in Compressed Sensing of Non-uniformly Sparse Signals, IEEE International Symposium on Information Theory (ISIT), Publisher: IEEE, Pages: 231-235

CONFERENCE PAPER

Ahmad BI, Al-Ani M, Tarczynski A, Dai W, Ling Cet al., 2013, COMPRESSIVE AND NON-COMPRESSIVE RELIABLE WIDEBAND SPECTRUM SENSING AT SUB-NYQUIST RATES, 21st European Signal Processing Conference (EUSIPCO), Publisher: IEEE

CONFERENCE PAPER

Dai W, Yueksel S, 2013, Observability of a Linear System Under Sparsity Constraints, IEEE TRANSACTIONS ON AUTOMATIC CONTROL, Vol: 58, Pages: 2372-2376, ISSN: 0018-9286

JOURNAL ARTICLE

Filos J, Karseras E, Dai W, Yan Set al., 2013, Tracking Dynamic Sparse Signals with Hierarchical Kalman Filters: A Case Study, 18th International Conference on Digital Signal Processing (DSP), Publisher: IEEE, ISSN: 1546-1874

CONFERENCE PAPER

Karseras E, Leung K, Dai W, 2013, TRACKING DYNAMIC SPARSE SIGNALS USING HIERARCHICAL BAYESIAN KALMAN FILTERS, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 6546-6550, ISSN: 1520-6149

CONFERENCE PAPER

Karseras E, Leung K, Dai W, 2013, HIERARCHICAL BAYESIAN KALMAN FILTERS FOR WIRELESS SENSOR NETWORKS, 21st European Signal Processing Conference (EUSIPCO), Publisher: IEEE

CONFERENCE PAPER

Xu T, Wang W, Dai W, 2013, Sparse coding with adaptive dictionary learning for underdetermined blind speech separation, SPEECH COMMUNICATION, Vol: 55, Pages: 432-450, ISSN: 0167-6393

JOURNAL ARTICLE

Zhao X, Zhou G, Dai W, 2013, SMOOTHED SIMCO FOR DICTIONARY LEARNING: HANDLING THE SINGULARITY ISSUE, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 3292-3296, ISSN: 1520-6149

CONFERENCE PAPER

Zhao X, Zhou G, Dai W, Xu T, Wang Wet al., 2013, JOINT IMAGE SEPARATION AND DICTIONARY LEARNING, 18th International Conference on Digital Signal Processing (DSP), Publisher: IEEE, ISSN: 1546-1874

CONFERENCE PAPER

Dai W, Kerman E, Milenkovic O, 2012, A Geometric Approach to Low-Rank Matrix Completion, IEEE TRANSACTIONS ON INFORMATION THEORY, Vol: 58, Pages: 237-247, ISSN: 0018-9448

JOURNAL ARTICLE

Dai W, Xu T, Wang W, 2012, Simultaneous Codeword Optimization (SimCO) for Dictionary Update and Learning, IEEE TRANSACTIONS ON SIGNAL PROCESSING, Vol: 60, Pages: 6340-6353, ISSN: 1053-587X

JOURNAL ARTICLE

Dai W, Xu T, Wang W, 2012, DICTIONARY LEARNING AND UPDATE BASED ON SIMULTANEOUS CODEWORD OPTIMIZATION (SIMCO), IEEE International Conference on Acoustics, Speech and Signal Processing, Publisher: IEEE, Pages: 2037-2040, ISSN: 1520-6149

CONFERENCE PAPER

Dai W, YĆ¼ksel S, 2012, Technical Report: Observability of a Linear System under Sparsity Constraints

Consider an n-dimensional linear system where it is known that there are atmost k<n non-zero components in the initial state. The observability problem,that is the recovery of the initial state, for such a system is considered. Weobtain sufficient conditions on the number of the available observations to beable to recover the initial state exactly for such a system. Both deterministicand stochastic setups are considered for system dynamics. In the formersetting, the system matrices are known deterministically, whereas in the lattersetting, all of the matrices are picked from a randomized class of matrices.The main message is that, one does not need to obtain full n observations to beable to uniquely identify the initial state of the linear system, even when theobservations are picked randomly, when the initial condition is known to besparse.

JOURNAL ARTICLE

Zhou G, Zhao X, Dai W, 2012, Low Rank Matrix Completion: A Smoothed l(0)-Search, 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton), Publisher: IEEE, Pages: 1010-1017, ISSN: 2474-0195

CONFERENCE PAPER

Dai W, Kerman E, Milenkovic O, 2011, Low-Rank Matrix Completion with Geometric Performance Guarantees, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 3740-3743, ISSN: 1520-6149

CONFERENCE PAPER

Dai W, Milenkovic O, 2011, Information Theoretical and Algorithmic Approaches to Quantized Compressive Sensing, IEEE TRANSACTIONS ON COMMUNICATIONS, Vol: 59, Pages: 1857-1866, ISSN: 0090-6778

JOURNAL ARTICLE

Dai W, Milenkovic O, Kerman E, 2011, Subspace Evolution and Transfer (SET) for Low-Rank Matrix Completion, IEEE TRANSACTIONS ON SIGNAL PROCESSING, Vol: 59, Pages: 3120-3132, ISSN: 1053-587X

JOURNAL ARTICLE

Hoa VP, Dai W, Milenkovic O, 2010, COMPRESSIVE LIST-SUPPORT RECOVERY FOR COLLUDER IDENTIFICATION, 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, Publisher: IEEE, Pages: 4166-4169, ISSN: 1520-6149

CONFERENCE PAPER

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