Publications
88 results found
Stankovic I, Dai W, 2016, Reconstruction of Global Ozone Density Data using a Gradient-Descent Algorithm, 58th ELMAR International Symposium, Publisher: IEEE, Pages: 85-88, ISSN: 1334-2630
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- Citations: 1
Zhou G, Dai W, 2016, An Approximate Message Passing Algorithm for Robust Face Recognition, 24th European Signal Processing Conference (EUSIPCO), Publisher: IEEE, Pages: 1262-1266, ISSN: 2076-1465
Lu Y, Dai W, 2016, Extended AMP Algorithm for Correlated Distributed Compressed Sensing Model, IEEE International Conference on Digital Signal Processing (DSP), Publisher: IEEE, Pages: 700-704
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- Citations: 1
Wu J, Lu Y, Dai W, 2016, Off-grid Compressed Sensing for WiFi-based Passive Radar, 16th IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), Publisher: IEEE, Pages: 258-262, ISSN: 2162-7843
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- Citations: 4
Ma Z, Dai W, Liu Y, et al., 2016, GROUP SPARSE BAYESIAN LEARNING VIA EXACT AND FAST MARGINAL LIKELIHOOD MAXIMIZATION, 41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Publisher: IEEE, Pages: 4508-4512, ISSN: 1520-6149
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- Citations: 1
Dong J, Wang W, Dai W, et al., 2015, Analysis SimCO Algorithms for Sparse Analysis Model Based Dictionary Learning, IEEE Transactions on Signal Processing, Vol: 64, Pages: 417-431, ISSN: 1941-0476
In this paper, we consider the dictionary learning problem for the sparse analysis model. A novel algorithm is proposed by adapting the simultaneous codeword optimization (SimCO) algorithm, based on the sparse synthesis model, to the sparse analysis model. This algorithm assumes that the analysis dictionary contains unit l2-norm atoms and learns the dictionary by optimization on manifolds. This framework allows multiple dictionary atoms to be updated simultaneously in each iteration. However, similar to several existing analysis dictionary learning algorithms, dictionaries learned by the proposed algorithm may contain similar atoms, leading to a degenerate (coherent) dictionary. To address this problem, we also consider restricting the coherence of the learned dictionary and propose Incoherent Analysis SimCO by introducing an atom decorrelation step following the update of the dictionary. We demonstrate the competitive performance of the proposed algorithms using experiments with synthetic data and image denoising as compared with existing algorithms.
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: 1557-9654
This paper provides a proof of global convergence of gradient search for low-rank matrix approximation. Such approximations have recently been of interest for large-scale problems, as well as for dictionary learning for sparse signal representations and matrix completion. The proof is based on the interpretation of the problem as an optimization on the Grassmann manifold and Fubiny-Study distance on this space.
Gao X, Li X, Filos J, et 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
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- Citations: 5
Ding W, Yang F, Dai W, et al., 2015, Time-Frequency Joint Sparse Channel Estimation for MIMO-OFDM Systems, IEEE COMMUNICATIONS LETTERS, Vol: 19, Pages: 58-61, ISSN: 1089-7798
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- Citations: 64
Zhu X, Dai L, Dai W, et 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
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- Citations: 13
Ding W, Lu Y, Yang F, et 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
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- Citations: 2
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
Gao Z, Dai L, Dai W, et 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
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- Citations: 8
Karseras E, Dai W, Dai L, et al., 2015, Fast Variational Bayesian Learning for Channel Estimation with Prior Statistical Information, 16th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Publisher: IEEE, Pages: 470-474, ISSN: 2325-3789
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- Citations: 5
Li P, Dai W, Meng H, et al., 2015, On Recovery of Sparse Signals with Block Structures, IEEE International Symposium on Information Theory (ISIT), Publisher: IEEE, Pages: 546-550
Zhu X, Dai L, Gui G, et al., 2015, Structured Matching Pursuit for Reconstruction of Dynamic Sparse Channels, IEEE Global Telecommunications Conference (GLOBECOM), Publisher: IEEE, ISSN: 2334-0983
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- Citations: 5
Zhao X, Dai W, 2015, On Joint Recovery of Sparse Signals with Common Supports, IEEE International Symposium on Information Theory (ISIT), Publisher: IEEE, Pages: 541-545
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- Citations: 4
Dong J, Wang W, Dai W, 2014, ANALYSIS SIMCO: A NEW ALGORITHM FOR ANALYSIS DICTIONARY LEARNING, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Publisher: IEEE, ISSN: 1520-6149
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- Citations: 1
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
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- Citations: 1
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
Zhao X, Zhou G, Dai W, et al., 2014, Blind Source Separation Based on Dictionary Learning: A Singularity-Aware Approach, BLIND SOURCE SEPARATION: ADVANCES IN THEORY, ALGORITHMS AND APPLICATIONS, Editors: Naik, Wang, Publisher: SPRINGER-VERLAG BERLIN, Pages: 39-59, ISBN: 978-3-642-55015-7
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- Citations: 3
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
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- Citations: 5
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
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- Citations: 19
Zhao X, Zhou G, Dai W, et al., 2013, JOINT IMAGE SEPARATION AND DICTIONARY LEARNING, 18th International Conference on Digital Signal Processing (DSP), Publisher: IEEE, ISSN: 1546-1874
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- Citations: 1
Karseras E, Leung K, Dai W, 2013, HIERARCHICAL BAYESIAN KALMAN FILTERS FOR WIRELESS SENSOR NETWORKS, 21st European Signal Processing Conference (EUSIPCO), Publisher: IEEE
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
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- Citations: 30
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
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- Citations: 1
Filos J, Karseras E, Dai W, et 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
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- Citations: 1
Ahmad BI, Al-Ani M, Tarczynski A, et al., 2013, COMPRESSIVE AND NON-COMPRESSIVE RELIABLE WIDEBAND SPECTRUM SENSING AT SUB-NYQUIST RATES, 21st European Signal Processing Conference (EUSIPCO), Publisher: IEEE
Zhou G, Zhao X, Dai W, 2012, Low Rank Matrix Completion: A Smoothed l<sub>0</sub>-Search, 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton), Publisher: IEEE, Pages: 1010-1017, ISSN: 2474-0195
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- Citations: 2
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