Generalized methods and solvers for noise removal from piecewise constant signals. II. New methods
暂无分享,去创建一个
[1] Teuta Pilizota,et al. A molecular brake, not a clutch, stops the Rhodobacter sphaeroides flagellar motor , 2009, Proceedings of the National Academy of Sciences.
[2] Michio Homma,et al. Direct observation of steps in rotation of the bacterial flagellar motor , 2005, Nature.
[3] D Marr,et al. Theory of edge detection , 1979, Proceedings of the Royal Society of London. Series B. Biological Sciences.
[4] John W. Tukey,et al. Exploratory Data Analysis. , 1979 .
[5] Varit Chaisinthop,et al. Semi-parametric compression of piecewise smooth functions , 2009, 2009 17th European Signal Processing Conference.
[6] E. Rowan,et al. Geologic Cross Section D-D' Through the Appalachian Basin from the Findlay Arch, Sandusky County, Ohio, to the Valley and Ridge Province, Hardy County, West Virginia , 2009 .
[7] D. Donoho,et al. Does median filtering truly preserve edges better than linear filtering , 2006, math/0612422.
[8] Pin T. Ng,et al. Quantile smoothing splines , 1994 .
[9] Carlo Cattani,et al. Haar wavelet-based technique for sharp jumps classification , 2004 .
[10] Emmanuel J. Candès,et al. Modern statistical estimation via oracle inequalities , 2006, Acta Numerica.
[11] C. H. Mehta,et al. Segmentation of well logs by maximum-likelihood estimation , 1990 .
[12] L. Rudin,et al. Nonlinear total variation based noise removal algorithms , 1992 .
[13] Holger Hoefling. A Path Algorithm for the Fused Lasso Signal Approximator , 2009, 0910.0526.
[14] Trevor Hastie,et al. The Elements of Statistical Learning , 2001 .
[15] Petar M. Djuric,et al. Automatic segmentation of piecewise constant signal by hidden Markov models , 1996, Proceedings of 8th Workshop on Statistical Signal and Array Processing.
[16] Koen Visscher,et al. An objective, model-independent method for detection of non-uniform steps in noisy signals , 2008, Comput. Phys. Commun..
[17] Hal J. Bloom. Next generation Geostationary Operational Environmental Satellite: GOES-R, the United States' advanced weather sentinel , 2009, Optical Engineering + Applications.
[18] Jitendra Malik,et al. Scale-Space and Edge Detection Using Anisotropic Diffusion , 1990, IEEE Trans. Pattern Anal. Mach. Intell..
[19] Stephan Didas,et al. Splines in Higher Order TV Regularization , 2006, International Journal of Computer Vision.
[20] Ursula Gather,et al. Robust Detail‐Preserving Signal Extraction , 2005 .
[21] Stéphane Mallat,et al. A Wavelet Tour of Signal Processing - The Sparse Way, 3rd Edition , 2008 .
[22] Mark W. Schmidt,et al. Fast Optimization Methods for L1 Regularization: A Comparative Study and Two New Approaches , 2007, ECML.
[23] Jeff A. Bilmes,et al. What HMMs Can Do , 2006, IEICE Trans. Inf. Syst..
[24] Fabio Rocca,et al. Modeling seismic impedance with Markov chains , 1980 .
[25] R. Koenker. Quantile Regression: Name Index , 2005 .
[26] Regularization Paths for Least Squares Problems with Generalized $\ell_1$ Penalties , 2010 .
[27] T. Chan,et al. Edge-preserving and scale-dependent properties of total variation regularization , 2003 .
[28] Ansgar Steland,et al. On detecting jumps in time series: nonparametric setting , 2004 .
[29] A. Iserles. A First Course in the Numerical Analysis of Differential Equations: Stiff equations , 2008 .
[30] Jérôme Darbon,et al. Image Restoration with Discrete Constrained Total Variation Part I: Fast and Exact Optimization , 2006, Journal of Mathematical Imaging and Vision.
[31] Stephen P. Boyd,et al. 1 Trend Filtering , 2009, SIAM Rev..
[32] Emmanuel J. Candès,et al. New multiscale transforms, minimum total variation synthesis: applications to edge-preserving image reconstruction , 2002, Signal Process..
[33] Roland Fried,et al. On the robust detection of edges in time series filtering , 2007, Comput. Stat. Data Anal..
[34] S. Mallat. A wavelet tour of signal processing , 1998 .
[35] P. Prandoni. Optimal segmentation techniques for piecewise stationary signals , 1999 .
[36] Ajay N. Jain,et al. Assembly of microarrays for genome-wide measurement of DNA copy number , 2001, Nature Genetics.
[37] Robert Tibshirani,et al. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.
[38] R. A. Kennedy,et al. Forward-backward non-linear filtering technique for extracting small biological signals from noise , 1991, Journal of Neuroscience Methods.
[39] Thomas Brox,et al. On the Equivalence of Soft Wavelet Shrinkage, Total Variation Diffusion, Total Variation Regularization, and SIDEs , 2004, SIAM J. Numer. Anal..
[40] S. McKinney,et al. Analysis of single-molecule FRET trajectories using hidden Markov modeling. , 2006, Biophysical journal.
[41] Yizong Cheng,et al. Mean Shift, Mode Seeking, and Clustering , 1995, IEEE Trans. Pattern Anal. Mach. Intell..
[42] Stephen P. Boyd,et al. Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.
[43] Tony F. Chan,et al. Image processing and analysis - variational, PDE, wavelet, and stochastic methods , 2005 .
[44] J. Suykens,et al. Convex Clustering Shrinkage , 2005 .
[45] Shin Ta Liu,et al. Nonlinear Signal Processing: A Statistical Approach , 2006, Technometrics.
[46] E. S. Page. A test for a change in a parameter occurring at an unknown point , 1955 .
[47] Stéphane Mallat,et al. Singularity detection and processing with wavelets , 1992, IEEE Trans. Inf. Theory.
[48] D. Gill. Application of a Statistical Zonation Method to Reservoir Evaluation and Digitized-Log Analysis , 1970 .
[49] S H Chung,et al. Characterization of single channel currents using digital signal processing techniques based on Hidden Markov Models. , 1990, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.
[50] Yazhen Wang. Jump and sharp cusp detection by wavelets , 1995 .
[51] J. Franklin,et al. The elements of statistical learning: data mining, inference and prediction , 2005 .
[52] Christy F Landes,et al. Denoising single-molecule FRET trajectories with wavelets and Bayesian inference. , 2010, Biophysical journal.
[53] Michael Elad,et al. On the origin of the bilateral filter and ways to improve it , 2002, IEEE Trans. Image Process..
[54] Gonzalo R. Arce,et al. Nonlinear Signal Processing - A Statistical Approach , 2004 .
[55] P. Mrázek,et al. ON ROBUST ESTIMATION AND SMOOTHING WITH SPATIAL AND TONAL KERNELS , 2006 .
[56] S. Rosset,et al. Piecewise linear regularized solution paths , 2007, 0708.2197.
[57] Jérôme Darbon,et al. Image Restoration with Discrete Constrained Total Variation Part II: Levelable Functions, Convex Priors and Non-Convex Cases , 2006, Journal of Mathematical Imaging and Vision.
[58] Klaus Nordhausen,et al. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition by Trevor Hastie, Robert Tibshirani, Jerome Friedman , 2009 .
[59] Liedewij Laan,et al. Assembly dynamics of microtubules at molecular resolution , 2006, Nature.
[60] Stéphane Mallat,et al. Characterization of Signals from Multiscale Edges , 2011, IEEE Trans. Pattern Anal. Mach. Intell..
[61] R. Tibshirani,et al. PATHWISE COORDINATE OPTIMIZATION , 2007, 0708.1485.
[62] B I Justusson,et al. Median Filtering: Statistical Properties , 1981 .
[63] Zoubin Ghahramani,et al. A Unifying Review of Linear Gaussian Models , 1999, Neural Computation.
[64] Larry D. Hostetler,et al. The estimation of the gradient of a density function, with applications in pattern recognition , 1975, IEEE Trans. Inf. Theory.
[65] Jean Serra,et al. Image Analysis and Mathematical Morphology , 1983 .
[66] Raymond H. Chan,et al. A Detection Statistic for Random-Valued Impulse Noise , 2007, IEEE Transactions on Image Processing.
[67] J CandèsEmmanuel,et al. New multiscale transforms, minimum total variation synthesis , 2002 .
[68] Kenneth Steiglitz,et al. Combinatorial Optimization: Algorithms and Complexity , 1981 .