Sparse reconstruction based on iterative TF domain filtering and Viterbi based IF estimation algorithm
暂无分享,去创建一个
[1] Irena Orovic,et al. A Tutorial on Sparse Signal Reconstruction and Its Applications in Signal Processing , 2018, Circuits Syst. Signal Process..
[2] Chuan Li,et al. A generalized synchrosqueezing transform for enhancing signal time-frequency representation , 2012, Signal Process..
[3] Srdjan Stankovic,et al. Instantaneous frequency in time-frequency analysis: Enhanced concepts and performance of estimation algorithms , 2014, Digit. Signal Process..
[4] Vahid Abolghasemi,et al. An improved design of adaptive directional time-frequency distributions based on the Radon transform , 2018, Signal Process..
[5] Guang Meng,et al. Separation of Overlapped Non-Stationary Signals by Ridge Path Regrouping and Intrinsic Chirp Component Decomposition , 2017, IEEE Sensors Journal.
[6] Yimin D. Zhang,et al. Sparsity-based frequency-hopping spectrum estimation with missing samples , 2016, 2016 IEEE Radar Conference (RadarConf).
[7] Daniele Borio,et al. Time-Frequency Analysis for GNSSs: From interference mitigation to system monitoring , 2017, IEEE Signal Processing Magazine.
[8] Branka Jokanovic,et al. Reduced Interference Sparse Time-Frequency Distributions for Compressed Observations , 2015, IEEE Transactions on Signal Processing.
[9] Milos Dakovic,et al. On the reconstruction of nonsparse time-frequency signals with sparsity constraint from a reduced set of samples , 2018, Signal Process..
[10] Sadiq Ali,et al. Sparsity-Aware Adaptive Directional Time–Frequency Distribution for Source Localization , 2017, Circuits Syst. Signal Process..
[11] Vahid Abolghasemi,et al. Locally Optimized Adaptive Directional Time–Frequency Distributions , 2018, Circuits Syst. Signal Process..
[12] Igor Djurovic,et al. QML-RANSAC Instantaneous Frequency Estimator for Overlapping Multicomponent Signals in the Time-Frequency Plane , 2018, IEEE Signal Processing Letters.
[13] F. Hlawatsch,et al. Linear and quadratic time-frequency signal representations , 1992, IEEE Signal Processing Magazine.
[14] J. Tropp,et al. CoSaMP: Iterative signal recovery from incomplete and inaccurate samples , 2008, Commun. ACM.
[15] Mike E. Davies,et al. Gradient Pursuits , 2008, IEEE Transactions on Signal Processing.
[16] LJubisa Stankovic,et al. An algorithm for the Wigner distribution based instantaneous frequency estimation in a high noise environment , 2004, Signal Process..
[17] Braham Himed,et al. Sparsity-based time-frequency representation of FM signals with burst missing samples , 2019, Signal Process..
[18] Joel A. Tropp,et al. Greed is good: algorithmic results for sparse approximation , 2004, IEEE Transactions on Information Theory.
[19] Nabeel Ali Khan,et al. Reconstruction of Non-stationary Signals with Missing Samples Using Time–frequency Filtering , 2018, Circuits Syst. Signal Process..
[20] Branka Jokanovic,et al. A sparsity-perspective to quadratic time-frequency distributions , 2015, Digit. Signal Process..
[21] Douglas L. Jones,et al. An adaptive optimal-kernel time-frequency representation , 1995, IEEE Trans. Signal Process..
[22] A. Papoulis. A new algorithm in spectral analysis and band-limited extrapolation. , 1975 .
[23] Po Li,et al. An improved Viterbi algorithm for IF extraction of multicomponent signals , 2018, Signal Image Video Process..
[24] Igor Djurovic,et al. A Modified Viterbi Algorithm-Based IF Estimation Algorithm for Adaptive Directional Time–Frequency Distributions , 2018, Circuits Syst. Signal Process..
[25] Sofia C. Olhede,et al. A generalized demodulation approach to time-frequency projections for multicomponent signals , 2005, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.
[26] Ljubiša Stanković,et al. Adaptive Variable Step Algorithm for Missing Samples Recovery in Sparse Signals , 2013, IET Signal Process..
[27] Sadiq Ali,et al. Instantaneous frequency estimation of intersecting and close multi-component signals with varying amplitudes , 2018, Signal Image Video Process..
[28] Ran Tao,et al. Structure-Aware Bayesian Compressive Sensing for Frequency-Hopping Spectrum Estimation With Missing Observations , 2016, IEEE Transactions on Signal Processing.