Li, T.F.[Tze Fen],
Chang, S.W.[Sung Wu],
A quick method for estimation of parameters of individual pulses in a
multipath signal,
PR(25), No. 12, December 1992, pp. 1529-1533.
Elsevier DOI
0401
BibRef
Vijayakumar, P.,
Gunavatohi, K.,
Efficient Energy Recovery for Positive Feedback Adiabatic Logic,
GVIP(05), No. V7, 2005, pp. xx-yy
HTML Version.
BibRef
0500
Gazor, S.,
Derakhtian, M.,
Tadaion, A.A.,
Computationally Efficient Maximum Likelihood Sequence Estimation and
Activity Detection for M-PSK Signals in Unknown Flat Fading Channels,
SPLetters(17), No. 10, October 2010, pp. 871-874.
IEEE DOI
1008
BibRef
Sugiura, S.,
Hanzo, L.,
Effects of Channel Estimation on Spatial Modulation,
SPLetters(19), No. 12, December 2012, pp. 805-808.
IEEE DOI
1212
BibRef
Khan, N.A.,
Boashash, B.,
Instantaneous Frequency Estimation of Multicomponent Nonstationary
Signals Using Multiview Time-Frequency Distributions Based on the
Adaptive Fractional Spectrogram,
SPLetters(20), No. 2, February 2013, pp. 157-160.
IEEE DOI
1302
BibRef
Stankovic, L.,
Stankovic, S.,
Orovic, I.,
Amin, M.G.,
Robust Time-Frequency Analysis Based on the L-Estimation and
Compressive Sensing,
SPLetters(20), No. 5, May 2013, pp. 499-502.
IEEE DOI
1304
BibRef
Huang, R.[Renke],
Zheng, H.[Hao],
Kuruoglu, E.E.[Ercan E.],
Time-varying ARMA stable process estimation using sequential Monte
Carlo,
SIViP(7), No. 5, September 2013, pp. 951-958.
Springer DOI
1309
BibRef
Zhu, Z.W.[Zhi-Wen],
Huang, X.P.[Xin-Ping],
Caron, M.,
Leung, H.,
A Blind AM/PM Estimation Method for Power Amplifier Linearization,
SPLetters(20), No. 11, 2013, pp. 1042-1045.
IEEE DOI
1310
higher order statistics
BibRef
Ren, X.T.[Xiao-Tian],
Xu, H.[Hui],
Huang, Z.T.[Zhi-Tao],
Wang, F.H.[Feng-Hua],
Wang, X.[Xiang],
Blind joint information and spreading sequence estimation for
short-code DS-SS signal in asynchronous and synchronous systems,
SIViP(7), No. 6, November 2013, pp. 1183-1194.
Springer DOI
1310
BibRef
Senejohnny, D.M.[Danial Mohammadi],
Delavari, H.[Hadi],
Linear estimator for fractional systems,
SIViP(8), No. 2, February 2014, pp. 389-396.
Springer DOI
1402
BibRef
Uhlich, S.,
Computing Jacobian and Hessian of Estimators and Their Application to
Risk Approximation,
SPLetters(21), No. 4, April 2014, pp. 469-472.
IEEE DOI
1403
Jacobian matrices
BibRef
Seelamantula, C.S.[Chandra Sekhar],
Shenoy, R.R.,
A Contraction Mapping Approach for Robust Estimation of Lagged
Autocorrelation,
SPLetters(21), No. 9, September 2014, pp. 1054-1058.
IEEE DOI
1406
Correlation
BibRef
Gupta, R.[Rinki],
Kumar, A.[Arun],
Bahl, R.[Rajendar],
Estimation of instantaneous frequencies using iterative empirical mode
decomposition,
SIViP(8), No. 5, July 2014, pp. 799-812.
Springer DOI
1407
BibRef
Liu, L.F.[Lu-Feng],
Du, X.P.[Xin-Peng],
Cheng, L.Z.[Li-Zhi],
Stable Signal Recovery via Randomly Enhanced Adaptive Subspace
Pursuit Method,
SPLetters(20), No. 8, 2013, pp. 823-826.
IEEE DOI
1307
adaptive signal processing
BibRef
McKilliam, R.G.,
Clarkson, I.V.L.,
Quinn, B.G.,
Fast Sparse Period Estimation,
SPLetters(22), No. 1, January 2015, pp. 62-66.
IEEE DOI
1410
Monte Carlo methods
BibRef
Hansson-Sandsten, M.,
Brynolfsson, J.,
The Scaled Reassigned Spectrogram with Perfect Localization for
Estimation of Gaussian Functions,
SPLetters(22), No. 1, January 2015, pp. 100-104.
IEEE DOI
1410
Gaussian processes
BibRef
So, J.,
Kim, D.,
Lee, Y.,
Sung, Y.,
Pilot Signal Design for Massive MIMO Systems:
A Received Signal-To-Noise-Ratio-Based Approach,
SPLetters(22), No. 5, May 2015, pp. 549-553.
IEEE DOI
1411
Channel estimation
BibRef
Shahmansoori, A.[Arash],
Consecutive adaptive blind estimation of timing offsets for arbitrary
channel time-interleaved ADCs,
SIViP(9), No. 1, January 2015, pp. 45-55.
Springer DOI
1503
analog-to-digital convertors.
BibRef
Shahmansoori, A.[Arash],
Adaptive blind calibration of timing offsets in a two-channel
time-interleaved analog-to-digital converter through Lagrange
interpolation,
SIViP(9), No. 5, July 2015, pp. 1047-1054.
WWW Link.
1506
BibRef
Elvira, V.,
Martino, L.,
Luengo, D.,
Bugallo, M.F.,
Efficient Multiple Importance Sampling Estimators,
SPLetters(22), No. 10, October 2015, pp. 1757-1761.
IEEE DOI
1506
computational complexity
BibRef
Yang, P.[Peng],
Liu, Z.[Zheng],
Jiang, W.L.[Wen-Li],
Parameter estimation of multi-component chirp signals based on discrete
chirp Fourier transform and population Monte Carlo,
SIViP(9), No. 5, July 2015, pp. 1137-1149.
WWW Link.
1506
BibRef
Guerrier, S.,
Molinari, R.,
Stebler, Y.,
Theoretical Limitations of Allan Variance-based Regression for Time
Series Model Estimation,
SPLetters(23), No. 5, May 2016, pp. 597-601.
IEEE DOI
1604
calibration
BibRef
Wang, G.[Guinan],
Zhang, H.J.[Hong-Juan],
Yu, S.W.[Shi-Wei],
Ding, S.X.[Shu-Xue],
A family of the subgradient algorithm with several cosparsity
inducing functions to the cosparse recovery problem,
PRL(80), No. 1, 2016, pp. 64-69.
Elsevier DOI
1609
Cosparse analysis model
BibRef
Göken, Ç.,
Gezici, S.,
Optimal Parameter Encoding Based on Worst Case Fisher Information
Under a Secrecy Constraint,
SPLetters(24), No. 11, November 2017, pp. 1611-1615.
IEEE DOI
1710
encoding, mean square error methods,
linear minimum MSE estimator, low-complexity algorithm,
BibRef
Wang, P.,
Orlik, P.V.,
Sadamoto, K.,
Tsujita, W.,
Gini, F.,
Parameter Estimation of Hybrid Sinusoidal FM-Polynomial Phase Signal,
SPLetters(24), No. 1, January 2017, pp. 66-70.
IEEE DOI
1702
frequency modulation
BibRef
Arriaga-Trejo, I.A.,
Orozco-Lugo, A.G.,
Villanueva-Maldonado, J.,
Flores-Troncoso, J.,
Joint I/Q imbalances estimation using data-dependent superimposed
training,
SIViP(11), No. 4, May 2017, pp. 729-736.
Springer DOI
1704
Joint estimation of the channel impulse response and
frequency-dependent in-phase and quadrature-phase (I/Q) imbalances.
BibRef
Wang, P.,
Orlik, P.V.,
Sadamoto, K.,
Tsujita, W.,
Sawa, Y.,
Cramer-Rao Bounds for a Coupled Mixture of Polynomial Phase and
Sinusoidal FM Signals,
SPLetters(24), No. 6, June 2017, pp. 746-750.
IEEE DOI
1609
polynomials, signal processing, CRB, Crame´r-Rao bounds,
polynomial phase signal, pure PPS case, sinusoidal FM signals,
Doppler radar, Frequency modulation, Indexes, Mixture models,
Parameter estimation.
BibRef
Tobar, F.,
Rios, G.,
Valdivia, T.,
Guerrero, P.,
Recovering Latent Signals From a Mixture of Measurements Using a
Gaussian Process Prior,
SPLetters(24), No. 2, February 2017, pp. 231-235.
IEEE DOI
1702
Bayes methods
BibRef
Wang, W.D.[Wen-Dong],
Wang, J.J.[Jian-Jun],
Zhang, Z.L.[Zi-Li],
Robust Signal Recovery With Highly Coherent Measurement Matrices,
SPLetters(24), No. 3, March 2017, pp. 304-308.
IEEE DOI
1702
Approximation algorithms
BibRef
Chen, S.J.[Shao-Jie],
Liu, K.[Kai],
Yang, Y.G.[Yu-Guang],
Xu, Y.T.[Yu-Ting],
Lee, S.[Seonjoo],
Lindquist, M.[Martin],
Caffo, B.S.[Brian S.],
Vogelstein, J.T.[Joshua T.],
An M-estimator for reduced-rank system identification,
PRL(86), No. 1, 2017, pp. 76-81.
Elsevier DOI
1702
High dimensional time-series data.
BibRef
Bendory, T.,
Eldar, Y.C.,
Recovery of Sparse Positive Signals on the Sphere from Low Resolution
Measurements,
SPLetters(22), No. 12, December 2015, pp. 2383-2386.
IEEE DOI
1512
convex programming
BibRef
Wan, Z.[Zhong],
Guo, J.[Jie],
Liu, J.J.[Jing-Jing],
Liu, W.Y.[Wei-Yi],
A modified spectral conjugate gradient projection method for signal
recovery,
SIViP(12), No. 8, November 2018, pp. 1455-1462.
Springer DOI
1809
Signal recovery.
BibRef
Perotti, L.C.,
Vrinceanu, D.,
Bessis, D.,
Recovery of the Starting Times of Delayed Signals,
SPLetters(25), No. 10, October 2018, pp. 1455-1459.
IEEE DOI
1810
iterative methods, signal processing, smoothing methods,
starting times, delayed signals, starting point, arbitrary number,
Padé approximant
BibRef
Bey, N.Y.[Nourédine Yahya],
Highly accurate frequency estimation of brief duration signals in noise,
SIViP(12), No. 7, October 2018, pp. 1279-1283.
WWW Link.
1809
BibRef
Horstmann, S.,
Ramírez, D.,
Schreier, P.J.,
Joint Detection of Almost-Cyclostationary Signals and Estimation of
Their Cycle Period,
SPLetters(25), No. 11, November 2018, pp. 1695-1699.
IEEE DOI
1811
channel bank filters, interpolation, signal detection,
signal sampling, cycle period, wide-sense stationary noise,
sample rate conversion
BibRef
Wang, X.,
Li, G.,
Varshney, P.K.,
Distributed Detection of Weak Signals From One-Bit Measurements Under
Observation Model Uncertainties,
SPLetters(26), No. 3, March 2019, pp. 415-419.
IEEE DOI
1903
maximum likelihood estimation, quantisation (signal),
signal detection, wireless sensor networks, one-bit data,
locally most powerful test
BibRef
Khan, N.A.[Nabeel Ali],
Mohammadi, M.[Mokhtar],
Ali, S.[Sadiq],
Instantaneous frequency estimation of intersecting and close
multi-component signals with varying amplitudes,
SIViP(13), No. 3, April 2019, pp. 517-524.
Springer DOI
1904
BibRef
Khan, S.A.,
Saleem, S.,
Hassan, S.A.,
Ilyas, M.U.,
An Improved Data-Aided Linear Estimator of Modulation Index for
Binary CPM Signals,
SPLetters(26), No. 5, May 2019, pp. 780-784.
IEEE DOI
1905
continuous phase modulation, error statistics,
estimation algorithm,
partial response
BibRef
Nichols, J.M.,
Hutchinson, M.N.,
Menkart, N.,
Cranch, G.A.,
Rohde, G.K.,
Time Delay Estimation Via Wasserstein Distance Minimization,
SPLetters(26), No. 6, June 2019, pp. 908-912.
IEEE DOI
1906
computational complexity, delay estimation, minimisation,
signal processing, linear time, time delay estimation,
Wasserstein distance
BibRef
Gan, M.,
Chen, X.,
Ding, F.,
Chen, G.,
Chen, C.L.P.,
Adaptive RBF-AR Models Based on Multi-Innovation Least Squares Method,
SPLetters(26), No. 8, August 2019, pp. 1182-1186.
IEEE DOI
1908
autoregressive processes, learning (artificial intelligence),
least mean squares methods, parameter estimation,
time series prediction
BibRef
Deprem, Z.[Zeynel],
Çetin, A.E.[A. Enis],
Arikan, O.[Orhan],
AM/FM signal estimation with micro-segmentation and polynomial fit,
SIViP(8), No. 3, March 2014, pp. 399-413.
Springer DOI
1403
BibRef
Muniraju, G.,
Tepedelenlioglu, C.,
Spanias, A.,
Consensus Based Distributed Spectral Radius Estimation,
SPLetters(27), 2020, pp. 1045-1049.
IEEE DOI
2007
Convergence, Eigenvalues and eigenfunctions, Packet loss,
Estimation, Distributed algorithms, Signal processing algorithms,
spectral radius
BibRef
Mohammadi, E.,
Gohari, A.,
Marvasti, F.,
A Square Root Sampling Law for Signal Recovery,
SPLetters(26), No. 4, April 2019, pp. 562-566.
IEEE DOI
1903
Noise measurement, Distortion, Distortion measurement,
Stochastic processes, Atmospheric measurements,
square root law
BibRef
Dlask, M.[Martin],
Kukal, J.[Jaromir],
Hurst exponent estimation from short time series,
SIViP(13), No. 2, March 2019, pp. 263-269.
Springer DOI
1904
Time series.
BibRef
Duan, J.B.[Jun-Bo],
Idier, J.[Jérôme],
Wang, Y.P.[Yu-Ping],
Wan, M.X.[Ming-Xi],
A Joint Least Squares and Least Absolute Deviation Model,
SPLetters(26), No. 4, April 2019, pp. 543-547.
IEEE DOI
1903
LASSO: Least absolute shrinkage and selection operator.
least squares approximations, signal restoration, JOLESALAD,
generalized LASSO, constrained LASSO, LASSO models,
ramp signal restoration
BibRef
Fosson, S.M.,
Abuabiah, M.,
Recovery of Binary Sparse Signals From Compressed Linear Measurements
via Polynomial Optimization,
SPLetters(26), No. 7, July 2019, pp. 1070-1074.
IEEE DOI
1906
Optimization, Noise measurement, Sparse matrices,
Compressed sensing, Image coding, Sensors, Programming,
sparse signal recovery
BibRef
Guo, J.,
Chen, H.,
Chen, S.,
Improved Kernel Recursive Least Squares Algorithm Based Online
Prediction for Nonstationary Time Series,
SPLetters(27), 2020, pp. 1365-1369.
IEEE DOI
2008
Signal processing algorithms, Kernel, Prediction algorithms,
Heuristic algorithms, Time series analysis, Dictionaries,
quantized kernel recursive least squares
BibRef
Nie, D.,
Xie, K.,
Zhou, F.,
Qiao, G.,
A Correlation Detection Method of Low SNR Based on
Multi-Channelization,
SPLetters(27), 2020, pp. 1375-1379.
IEEE DOI
2008
Correlation, Signal to noise ratio, Signal processing algorithms,
Signal detection, Detection algorithms, Analytical models,
time-varying signal
BibRef
Garg, K.,
Baranwal, M.,
CAPPA: Continuous-Time Accelerated Proximal Point Algorithm for
Sparse Recovery,
SPLetters(27), 2020, pp. 1760-1764.
IEEE DOI
2010
Convergence, Heuristic algorithms, Signal processing algorithms,
Machine learning algorithms, Convex functions, Acceleration,
signal reconstruction
BibRef
Harel, N.[Nadav],
Routtenberg, T.[Tirza],
Bayesian Post-Model-Selection Estimation,
SPLetters(28), 2021, pp. 175-179.
IEEE DOI
2102
Estimation, Bayes methods, Probability density function,
Parameter estimation, Computational modeling,
sparse recovery
BibRef
Cheng, Y.Y.[Yi-Yao],
Liu, L.[Lei],
Ping, L.[Li],
An Integral-Based Approach to Orthogonal AMP,
SPLetters(28), 2021, pp. 194-198.
IEEE DOI
2102
Monte Carlo methods, Training, Signal processing algorithms,
Binary phase shift keying, Software algorithms, Sensors,
state evolution
BibRef
Rupniewski, M.W.,
Reconstruction of Periodic Signals From Asynchronous Trains of
Samples,
SPLetters(28), 2021, pp. 289-293.
IEEE DOI
2102
Random variables, Signal reconstruction,
Signal processing algorithms, Sensors, Probabilistic logic, Shape,
signal sampling
BibRef
Jiang, L.[Li],
Zhou, J.[Junni],
Yang, R.L.[Run-Ling],
Liu, L.[Li],
Li, L.[Lin],
Parameter estimation of LFMCW signal using S-Method with adaptive
window,
ICIVC17(875-878)
IEEE DOI
1708
Estimation, Frequency estimation, Frequency modulation,
Signal to noise ratio, Time-frequency analysis, Transforms,
S-Method, adaptive window,
linear frequency modulated continuous wave,
short-time fourier transform, time frequency analysis.
BibRef
Gkoktsi, K.,
Tau Siesakul, B.,
Giaralis, A.,
Multi-channel sub-Nyquist cross-spectral estimation for modal
analysis of vibrating structures,
WSSIP15(287-290)
IEEE DOI
1603
acceleration measurement
BibRef
Narayanan, S.,
Sahoo, S.K.,
Makur, A.,
Recovery of correlated sparse signals using adaptive backtracking
matching pursuit,
VCIP15(1-4)
IEEE DOI
1605
Correlated sparse signals
BibRef
Ravelomanantsoa, A.,
Rabah, H.,
Rouane, A.,
Fast and efficient signals recovery for deterministic compressive
sensing: Applications to biosignals,
DASIP15(1-6)
IEEE DOI
1605
compressed sensing
BibRef
Sarjanoja, S.,
Boutellier, J.,
Hannuksela, J.,
BM3D image denoising using heterogeneous computing platforms,
DASIP15(1-8)
IEEE DOI
1605
filtering theory
BibRef
Liu, S.[Song],
Yamada, M.[Makoto],
Collier, N.[Nigel],
Sugiyama, M.[Masashi],
Change-Point Detection in Time-Series Data by Relative Density-Ratio
Estimation,
SSSPR12(363-372).
Springer DOI
1211
BibRef
Jibia, A.U.,
Salami, M.J.E.,
Khalifa, O.O.,
Elfaki, F.,
Cramer-Rao Lower Bound for Parameter Estimation of Multiexponential
Signals,
WSSIP09(1-5).
IEEE DOI
0906
BibRef
Wen, F.[Fei],
Wan, Q.[Qun],
Time Delay Estimation Based on Mutual Information Estimation,
CISP09(1-5).
IEEE DOI
0910
BibRef
Li, X.M.[Xue Mei],
Tao, R.[Ran],
Wang, Y.[Yue],
Time Delay Estimation Based on the Fractional Fourier Transform in the
Passive System,
CISP09(1-4).
IEEE DOI
0910
BibRef
Wang, T.[Tao],
Wan, Q.[Qun],
Sparse Signal Recovery via Multi-Residual Based Greedy Method,
CISP09(1-4).
IEEE DOI
0910
BibRef
Li, Z.L.[Zhi-Lin],
Chen, H.[Houjin],
Yao, C.[Chang],
Li, J.[Jupeng],
Yang, N.[Na],
Sparse Signal Recovery via Optimized Orthogonal Matching Pursuit,
CISP09(1-4).
IEEE DOI
0910
BibRef
Nelson, D.,
Loughlin, P.J.,
Cristobal, G.,
Cohen, L.[Leon],
Time-frequency methods for biological signal estimation,
ICPR00(Vol III: 110-114).
IEEE DOI
0403
BibRef
Chapter on New Unsorted Entries, and Other Miscellaneous Papers continues in
Network Analysis, Wireless, Network Intrusion .