Digital Signal Processing Reference
In-Depth Information
Chen, J., and Huo, X.: 2006, Theoretical results on sparse representations for multiple mea-
surement vectors, IEEE Transactions on Signal Processing 54(12), 4634-4643.
Chen, S. S., Donoho, D. L., and Saunders, M. A.: 1999, Atomic decomposition by basis pur-
suit, SIAM Journal on Scientific Computing 20(1), 33-61.
Chesneau, C., and Hebiri, M.: 2008, Some theoretical results on the grouped variables Lasso,
Mathematical Methods of Statistics 17(4), 317-326.
Chesneau, C., Fadili, M. J., and Starck, J.-L.: 2010, Stein block thresholding for image denois-
ing, Applied and Computational Harmonic Analysis 28(1), 67-88.
Christensen, O.: 2002, An Introduction to Frames and Riesz Bases ,Birkhauser, Boston.
Chui, C.: 1992, Wavelet Analysis and Its Applications , Academic Press, San Diego, CA.
Cichocki, A., and Amari, S.: 2002, Adaptive Blind Signal and Image Processing: Learning
Algorithms and Applications , John Wiley, New York.
Claypoole, R., Davis, G., Sweldens, W., and Baraniuk, R.: 2003, Nonlinear wavelet transforms
for image coding via lifting, IEEE Transactions on Image Processing 12(12), 1449-1459.
Cohen, A.: 2003, Numerical Analysis of Wavelet Methods , Elsevier, New York.
Cohen, A., Daubechies, I., and Feauveau, J.: 1992, Biorthogonal bases of compactly sup-
ported wavelets, Communications in Pure and Applied Mathematics 45, 485-560.
Cohen, A., DeVore, R., Petrushev, P., and Xu, H.: 1999, Nonlinear approximation and the
space BV( R 2 ), American Journal of Mathematics 121, 587-628.
Cohen, A., Dahmen, W., and DeVore, R.: 2009, Compressed sensing and best k -term approx-
imation, Journal of the American Mathematical Society 22, 211-231.
Coifman, R., and Donoho, D.: 1995, Translation invariant de-noising, in A. Antoniadis and
G. Oppenheim (eds.), Wavelets and Statistics , 125-150, Springer, New York.
Coifman, R., and Wickerhauser, M.: 1992, Entropy-based algorithms for best basis selection,
IEEE Transactions on Information Theory 38, 713-718.
Coifman, R., Meyer, Y., and Wickerhauser, M.: 1992, Wavelet analysis and signal processing,
in M. Ruskai, G. Beylkin, R. Coifman, I. Daubechies, S. Mallat, Y. Meyer, and L. Raphael
(eds.), Wavelets and Their Applications , 153-178, Jones and Bartlett, Boston.
Coifman, R., Geshwind, F., and Meyer, Y.: 2001, Noiselets, Applied and Computational
Harmonic Analysis 10(1), 27-44.
Combettes, P. L.: 2004, Solving monotone inclusions via compositions of nonexpansive aver-
aged operators, Optimization 53(5-6), 475-504.
Combettes, P., and Pesquet, J.-C.: 2007a, A Douglas-Rachford splitting approach to nons-
mooth convex variational signal recovery, IEEE Journal of Selected Topics in Signal Pro-
cessing 1(2), 564-574.
Combettes, P. L., and Pesquet, J.-C.: 2007b, Proximal thresholding algorithm for minimiza-
tion over orthonormal bases, SIAM Journal on Optimization 18(4), 1351-1376.
Combettes, P. L., and Pesquet, J.-C.: 2008, A proximal decomposition method for solving
convex variational inverse problems, Inverse Problems 24(6), 065014.
Combettes, P. L., and Wajs, V. R.: 2005, Signal recovery by proximal forward-backward split-
ting, Multiscale Modeling and Simulation 4(4), 1168-1200.
Comon, P.: 1994, Independent component analysis, a new concept?, Signal Processing 36(3),
287-314.
Cotter, S., Rao, B., Engan, K., and Kreutz-Delgado, K.: 2005, Sparse solutions to linear in-
verse problems with multiple measurement vectors, IEEE Transactions on Signal Process-
ing 53, 2477-2488.
Coupinot, G., Hecquet, J., Auriere, M., and Futaully, R.: 1992, Photometric analysis of astro-
nomical images by the wavelet transform, Astronomy and Astrophysics 259, 701-710.
Criminisi, A., Perez, P., and Toyama, K.: 2004, Region filling and object removal by examplar-
based image inpainting, IEEE Transactions on Image Processing 13(9), 1200-1212.
Crittenden, R. G.: 2000, Igloo pixelations of the sky, Astrophysical Letters and Communica-
tions 37, 377-382.
Curvelab: 2005, Second generation curvelet toolbox, http://www.curvelet.org.
Search WWH ::




Custom Search