Geometrical multi-resolution network based on ridgelet frame
Tài liệu tham khảo
McCulloch, 1943, A logical calculus of the ideas immanent in nervous activity, Bull. Math. Biophys., 5, 115, 10.1007/BF02478259
Cybenko, 1989, Approximation by superpositions of a Sigmoidal function, Math. Control Signals Syst., 2, 303, 10.1007/BF02551274
Park, 1991, Universal approximation using radial-basis-function networks, Neural Comput., 3, 246, 10.1162/neco.1991.3.2.246
Zhang, 1992, Wavelet networks, IEEE Trans. Neural Networks, 3, 889, 10.1109/72.165591
Barron, 1993, Universal approximation bounds for superpositions of a sigmoidal function, IEEE Trans. Inform. Theory, 39, 930, 10.1109/18.256500
Friedman, 1981, Projection pursuit regression, J. Am. Stat. Assoc., 76, 817, 10.2307/2287576
Hubel, 1962, Receptive fields, binocular interaction and functional architecture in the cat's visual cortex, J. Physiol., 160, 106, 10.1113/jphysiol.1962.sp006837
Olshausen, 1996, Emergence of simple cell receptive field properties by learning a sparse code for natural images, Nature, 381, 607, 10.1038/381607a0
E.J. Candès, Ridgelet: theory and applications, Ph.D. Dissertation, Stanford University, 1998.
Candès, 1999, Ridgelets: a key to higher-dimensional intermittency?, Philos. Trans. R. Soc. Lond. A., 357, 2495, 10.1098/rsta.1999.0444
Do, 2003, The finite ridgelet transform for image representation, IEEE Trans. Image Process., 12, 16, 10.1109/TIP.2002.806252
Yang, 2005, Identification of road signs using a new ridgelet network, ISCAS, 4, 3619
Yang, 2005, A directional multi-resolution ridgelet network, IJCNN, 2, 1331
Candès, 1999, Ridgelets and the representation of mutilated sobolev functions, SIAM J. Math. Anal., 33, 2495
Patrizio, 2004, Robust digital watermarking in the ridgelet domain, IEEE Signal Process. Lett., 11, 826, 10.1109/LSP.2004.835463
Z. Yao, N. Rajpoot, Ridgelet signature for image authentication, International Conference on Image Processing, 2004.
Donoho, 1999, Tight frames of k-plane ridgelets and the problem of representing objects that are smooth away from d-dimensional singularities in Rn, Proc. Natl. Acad. Sci. USA, 96, 1828, 10.1073/pnas.96.5.1828
Donoho, 2000, Orthonormal ridgelets and linear singularities, SIMA J. Math. Anal., 31, 1062, 10.1137/S0036141098344403
Grochenig, 1993, Acceleration of the frame algorithm, IEEE Trans. Signal Process., 41, 3331, 10.1109/78.258077
J.H. Holland, Genetic algorithms and classifier systems: foundations and their applications, in: Proceedings of the Second International Conference on Genetic Algorithms, 1987, pp. 82–89.
Dragotti, 2000, Compression of multispectral images by three-dimensional SPIHT algorithm, IEEE Trans. Geosci. Remote Sensing, 38, 416, 10.1109/36.823937
Zeng, 2001, SAR image data compression using a tree-structured wavelet transform, IEEE Trans. Geosci. Remote Sensing, 19, 546, 10.1109/36.911112
R. Kohno, M. Arai, H. Imai, Image compression using a neural network with learning capability of variable function of a neural unit, SPIE vol. 1360, Visual Communications and Image Processing ‘90, 1990, pp. 69–75.