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2017 | OriginalPaper | Chapter

The Restricted Isometry Property of Subsampled Fourier Matrices

Authors : Ishay Haviv, Oded Regev

Published in: Geometric Aspects of Functional Analysis

Publisher: Springer International Publishing

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Abstract

A matrix \(A \in \mathbb{C}^{q\times N}\) satisfies the restricted isometry property of order k with constant ε if it preserves the 2 norm of all k-sparse vectors up to a factor of 1 ±ε. We prove that a matrix A obtained by randomly sampling q = O(k ⋅ log2 k ⋅ logN) rows from an N × N Fourier matrix satisfies the restricted isometry property of order k with a fixed ε with high probability. This improves on Rudelson and Vershynin (Comm Pure Appl Math, 2008), its subsequent improvements, and Bourgain (GAFA Seminar Notes, 2014).

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Footnotes
1
A preliminary version appeared in Proceedings of the 27th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), 2016, pages 288–297.
 
2
Note that the list-decoding result of [14] was later improved by Wootters [33] using different techniques.
 
3
The result in [19] is weaker in two main respects. First, it is restricted to the case that Ax is in {0, 1} q . This significantly simplifies the analysis and leads to a better bound on the number of rows of A. Second, the order of quantifiers is switched, namely it shows that for any sparse x, a random subsampled A works with high probability, whereas for the restricted isometry property we need to show that a random A works for all sparse x.
 
Literature
1.
go back to reference N. Ailon, B. Chazelle, The fast Johnson–Lindenstrauss transform and approximate nearest neighbors. SIAM J. Comput. 39 (1), 302–322 (2009). Preliminary version in STOC’06 N. Ailon, B. Chazelle, The fast Johnson–Lindenstrauss transform and approximate nearest neighbors. SIAM J. Comput. 39 (1), 302–322 (2009). Preliminary version in STOC’06
2.
go back to reference N. Ailon, E. Liberty, Fast dimension reduction using Rademacher series on dual BCH codes. Discrete Comput. Geom. 42 (4), 615–630 (2009). Preliminary version in SODA’08 N. Ailon, E. Liberty, Fast dimension reduction using Rademacher series on dual BCH codes. Discrete Comput. Geom. 42 (4), 615–630 (2009). Preliminary version in SODA’08
3.
go back to reference N. Ailon, E. Liberty, An almost optimal unrestricted fast Johnson–Lindenstrauss transform. ACM Trans. Algorithms 9 (3), 21 (2013). Preliminary version in SODA’11 N. Ailon, E. Liberty, An almost optimal unrestricted fast Johnson–Lindenstrauss transform. ACM Trans. Algorithms 9 (3), 21 (2013). Preliminary version in SODA’11
4.
go back to reference A.S. Bandeira, E. Dobriban, D.G. Mixon, W.F. Sawin, Certifying the restricted isometry property is hard. IEEE Trans. Inform. Theory 59 (6), 3448–3450 (2013)MathSciNetCrossRef A.S. Bandeira, E. Dobriban, D.G. Mixon, W.F. Sawin, Certifying the restricted isometry property is hard. IEEE Trans. Inform. Theory 59 (6), 3448–3450 (2013)MathSciNetCrossRef
5.
go back to reference A.S. Bandeira, M.E. Lewis, D.G. Mixon, Discrete uncertainty principles and sparse signal processing. CoRR abs/1504.01014 (2015) A.S. Bandeira, M.E. Lewis, D.G. Mixon, Discrete uncertainty principles and sparse signal processing. CoRR abs/1504.01014 (2015)
6.
go back to reference R. Baraniuk, M. Davenport, R. DeVore, M. Wakin, A simple proof of the restricted isometry property for random matrices. Constr. Approx. 28 (3), 253–263 (2008)MathSciNetCrossRefMATH R. Baraniuk, M. Davenport, R. DeVore, M. Wakin, A simple proof of the restricted isometry property for random matrices. Constr. Approx. 28 (3), 253–263 (2008)MathSciNetCrossRefMATH
7.
go back to reference J. Bourgain, An improved estimate in the restricted isometry problem, in Geometric Aspects of Functional Analysis. Lecture Notes in Mathematics, vol. 2116, pp. 65–70 (Springer, Berlin, 2014) J. Bourgain, An improved estimate in the restricted isometry problem, in Geometric Aspects of Functional Analysis. Lecture Notes in Mathematics, vol. 2116, pp. 65–70 (Springer, Berlin, 2014)
8.
go back to reference E.J. Candès, The restricted isometry property and its implications for compressed sensing. C. R. Math. 346 (9–10), 589–592 (2008)MathSciNetCrossRefMATH E.J. Candès, The restricted isometry property and its implications for compressed sensing. C. R. Math. 346 (9–10), 589–592 (2008)MathSciNetCrossRefMATH
10.
go back to reference E.J. Candès, T. Tao, Near-optimal signal recovery from random projections: universal encoding strategies? IEEE Trans. on Inform. Theory 52 (12), 5406–5425 (2006)MathSciNetCrossRefMATH E.J. Candès, T. Tao, Near-optimal signal recovery from random projections: universal encoding strategies? IEEE Trans. on Inform. Theory 52 (12), 5406–5425 (2006)MathSciNetCrossRefMATH
11.
go back to reference E.J. Candès, M. Rudelson, T. Tao, R. Vershynin, Error correction via linear programming, in 46th Annual IEEE Symposium on Foundations of Computer Science, FOCS, pp. 295–308 (2005) E.J. Candès, M. Rudelson, T. Tao, R. Vershynin, Error correction via linear programming, in 46th Annual IEEE Symposium on Foundations of Computer Science, FOCS, pp. 295–308 (2005)
12.
go back to reference E.J. Candès, J.K. Romberg, T. Tao, Stable signal recovery from incomplete and inaccurate measurements. Commun. Pure Appl. Math. 59 (8), 1207–1223 (2006)MathSciNetCrossRefMATH E.J. Candès, J.K. Romberg, T. Tao, Stable signal recovery from incomplete and inaccurate measurements. Commun. Pure Appl. Math. 59 (8), 1207–1223 (2006)MathSciNetCrossRefMATH
14.
go back to reference M. Cheraghchi, V. Guruswami, A. Velingker, Restricted isometry of Fourier matrices and list decodability of random linear codes. SIAM J. Comput. 42 (5), 1888–1914 (2013). Preliminary version in SODA’13 M. Cheraghchi, V. Guruswami, A. Velingker, Restricted isometry of Fourier matrices and list decodability of random linear codes. SIAM J. Comput. 42 (5), 1888–1914 (2013). Preliminary version in SODA’13
15.
16.
go back to reference D.L. Donoho, M. Elad, V.N. Temlyakov, Stable recovery of sparse overcomplete representations in the presence of noise. IEEE Trans. Inform. Theory 52 (1), 6–18 (2006)MathSciNetCrossRefMATH D.L. Donoho, M. Elad, V.N. Temlyakov, Stable recovery of sparse overcomplete representations in the presence of noise. IEEE Trans. Inform. Theory 52 (1), 6–18 (2006)MathSciNetCrossRefMATH
17.
go back to reference S. Foucart, A. Pajor, H. Rauhut, T. Ullrich, The Gelfand widths of ℓ p -balls for 0 < p ≤ 1. J. Complex. 26 (6), 629–640 (2010) S. Foucart, A. Pajor, H. Rauhut, T. Ullrich, The Gelfand widths of p -balls for 0 < p ≤ 1. J. Complex. 26 (6), 629–640 (2010)
18.
go back to reference A.Y. Garnaev, E.D. Gluskin, On the widths of Euclidean balls. Sov. Math. Dokl. 30, 200–203 (1984)MATH A.Y. Garnaev, E.D. Gluskin, On the widths of Euclidean balls. Sov. Math. Dokl. 30, 200–203 (1984)MATH
19.
go back to reference I. Haviv, O. Regev, The list-decoding size of Fourier-sparse boolean functions, in Proceedings of the 30th Conference on Computational Complexity, CCC, pp. 58–71 (2015) I. Haviv, O. Regev, The list-decoding size of Fourier-sparse boolean functions, in Proceedings of the 30th Conference on Computational Complexity, CCC, pp. 58–71 (2015)
20.
go back to reference P. Indyk, I. Razenshteyn, On model-based RIP-1 matrices, in Automata, Languages, and Programming - 40th International Colloquium, ICALP, pp. 564–575 (2013) P. Indyk, I. Razenshteyn, On model-based RIP-1 matrices, in Automata, Languages, and Programming - 40th International Colloquium, ICALP, pp. 564–575 (2013)
21.
go back to reference A.C. Kak, M. Slaney, Principles of Computerized Tomographic Imaging (Society of Industrial and Applied Mathematics, Philadelphia, 2001)CrossRefMATH A.C. Kak, M. Slaney, Principles of Computerized Tomographic Imaging (Society of Industrial and Applied Mathematics, Philadelphia, 2001)CrossRefMATH
22.
go back to reference F. Krahmer, R. Ward, New and improved Johnson-Lindenstrauss embeddings via the restricted isometry property. SIAM J. Math. Anal. 43 (3), 1269–1281 (2011)MathSciNetCrossRefMATH F. Krahmer, R. Ward, New and improved Johnson-Lindenstrauss embeddings via the restricted isometry property. SIAM J. Math. Anal. 43 (3), 1269–1281 (2011)MathSciNetCrossRefMATH
23.
go back to reference F. Krahmer, S. Mendelson, H. Rauhut, Suprema of chaos processes and the restricted isometry property. CoRR abs/1207.0235 (2012) F. Krahmer, S. Mendelson, H. Rauhut, Suprema of chaos processes and the restricted isometry property. CoRR abs/1207.0235 (2012)
24.
go back to reference C. McDiarmid, Concentration, in Probabilistic Methods for Algorithmic Discrete Mathematics. Algorithms Combination, vol. 16 (Springer, Berlin, 1998), pp. 195–248 C. McDiarmid, Concentration, in Probabilistic Methods for Algorithmic Discrete Mathematics. Algorithms Combination, vol. 16 (Springer, Berlin, 1998), pp. 195–248
25.
go back to reference A. Natarajan, Y. Wu, Computational complexity of certifying restricted isometry property, in Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, APPROX, pp. 371–380 (2014) A. Natarajan, Y. Wu, Computational complexity of certifying restricted isometry property, in Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, APPROX, pp. 371–380 (2014)
26.
go back to reference D. Needell, J.A. Tropp, CoSaMP: iterative signal recovery from incomplete and inaccurate samples. Commun. ACM 53 (12), 93–100 (2010)CrossRefMATH D. Needell, J.A. Tropp, CoSaMP: iterative signal recovery from incomplete and inaccurate samples. Commun. ACM 53 (12), 93–100 (2010)CrossRefMATH
27.
go back to reference J. Nelson, E. Price, M. Wootters, New constructions of RIP matrices with fast multiplication and fewer rows, in Proceedings of the 25th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA, pp. 1515–1528 (2014) J. Nelson, E. Price, M. Wootters, New constructions of RIP matrices with fast multiplication and fewer rows, in Proceedings of the 25th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA, pp. 1515–1528 (2014)
28.
go back to reference D.G. Nishimura, Principles of Magnetic Resonance Imaging (Stanford University, Stanford, CA, 2010) D.G. Nishimura, Principles of Magnetic Resonance Imaging (Stanford University, Stanford, CA, 2010)
29.
go back to reference H. Rauhut, Compressive sensing and structured random matrices, in Theoretical Foundations and Numerical Methods for Sparse Recovery, vol. 9, ed. by M. Fornasier (De Gruyter, Berlin, 2010), pp. 1–92 H. Rauhut, Compressive sensing and structured random matrices, in Theoretical Foundations and Numerical Methods for Sparse Recovery, vol. 9, ed. by M. Fornasier (De Gruyter, Berlin, 2010), pp. 1–92
30.
go back to reference M. Rudelson, R. Vershynin, On sparse reconstruction from Fourier and Gaussian measurements. Commun. Pure Appl. Math. 61 (8), 1025–1045 (2008). Preliminary version in CISS’06 M. Rudelson, R. Vershynin, On sparse reconstruction from Fourier and Gaussian measurements. Commun. Pure Appl. Math. 61 (8), 1025–1045 (2008). Preliminary version in CISS’06
31.
go back to reference A.M. Tillmann, M.E. Pfetsch, The computational complexity of the restricted isometry property, the nullspace property, and related concepts in compressed sensing. IEEE Trans. Inform. Theory 60 (2), 1248–1259 (2014)MathSciNetCrossRef A.M. Tillmann, M.E. Pfetsch, The computational complexity of the restricted isometry property, the nullspace property, and related concepts in compressed sensing. IEEE Trans. Inform. Theory 60 (2), 1248–1259 (2014)MathSciNetCrossRef
32.
go back to reference S. Wenger, S. Darabi, P. Sen, K. Glassmeier, M.A. Magnor, Compressed sensing for aperture synthesis imaging, in Proceedings of the International Conference on Image Processing, ICIP, pp. 1381–1384 (2010) S. Wenger, S. Darabi, P. Sen, K. Glassmeier, M.A. Magnor, Compressed sensing for aperture synthesis imaging, in Proceedings of the International Conference on Image Processing, ICIP, pp. 1381–1384 (2010)
33.
go back to reference M. Wootters, On the list decodability of random linear codes with large error rates, in Proceedings of the 45th Annual ACM Symposium on Theory of Computing, STOC, pp. 853–860 (2013) M. Wootters, On the list decodability of random linear codes with large error rates, in Proceedings of the 45th Annual ACM Symposium on Theory of Computing, STOC, pp. 853–860 (2013)
Metadata
Title
The Restricted Isometry Property of Subsampled Fourier Matrices
Authors
Ishay Haviv
Oded Regev
Copyright Year
2017
DOI
https://doi.org/10.1007/978-3-319-45282-1_11

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