Riesz sequence

In mathematics, a sequence of vectors (xn) in a Hilbert space is called a Riesz sequence if there exist constants such that for every finite scalar sequence and hence, for all .[1][2]

A Riesz sequence is called a Riesz basis if Equivalently, a Riesz basis for is a family of the form , where is an orthonormal basis for and is a bounded bijective operator. Subsequently, there exist constants such that[3] Hence, Riesz bases need not be orthonormal, i.e., they are a generalization of orthonormal bases.[4]

Paley-Wiener criterion

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Let be an orthonormal basis for a Hilbert space and let be "close" to in the sense that

for some constant , , and arbitrary scalars . Then is a Riesz basis for .[5][6]

Theorems

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If H is a finite-dimensional space, then every basis of H is a Riesz basis.

Let be in the Lp space L2(R), let

and let denote the Fourier transform of . Define constants c and C with . Then the following are equivalent:[7]

The first of the above conditions is the definition for () to form a Riesz basis for the space it spans.

Kadec 1/4 Theorem

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The Kadec 1/4 theorem, sometimes called the Kadets 1/4 theorem, provides a specific condition under which a sequence of complex exponentials forms a Riesz basis for the Lp space . It is a foundational result in the theory of non-harmonic Fourier series.

Let be a sequence of real numbers such that

Then the sequence of complex exponentials forms a Riesz basis for .[8]

This theorem demonstrates the stability of the standard orthonormal basis (up to normalization) under perturbations of the frequencies .

The constant 1/4 is sharp; if , the sequence may fail to be a Riesz basis, such as:[9]When are allowed to be complex, the theorem holds under the condition . Whether the constant is sharp is an open question.[9]

See also

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Notes

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  1. ^ Christensen 2016, pp. 89–92.
  2. ^ Balazs, Stoeva & Antoine 2010, p. 3.
  3. ^ Christensen 2016, pp. 86–87.
  4. ^ Antoine & Balazs 2012.
  5. ^ Young 2001, p. 35.
  6. ^ Paley & Wiener 1934, p. 100.
  7. ^ Hernandez & Weiss 1996, chpt. 2.1 Multiresolution analysis.
  8. ^ Young 2001, p. 36.
  9. ^ a b Young 2001, p. 37.

References

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  • Antoine, J.-P.; Balazs, P. (2012). "Frames, Semi-Frames, and Hilbert Scales". Numerical Functional Analysis and Optimization. 33 (7–9): 736–769. arXiv:1203.0506. doi:10.1080/01630563.2012.682128. ISSN 0163-0563.
  • Balazs, Peter; Stoeva, Diana T.; Antoine, Jean-Pierre (2010). "Classification of General Sequences by Frame-Related Operators". Sampling Theory in Signal and Image Processing. 10 (1–2): 151–170. arXiv:1009.1496. doi:10.1007/BF03549539.
  • Christensen, Ole (2016). An Introduction to Frames and Riesz Bases. Applied and Numerical Harmonic Analysis. Cham: Springer International Publishing. doi:10.1007/978-3-319-25613-9. ISBN 978-3-319-25611-5.
  • Hernandez, Eugenio; Weiss, Guido (1996). A First Course on Wavelets. CRC Press. ISBN 978-0-8493-8274-1.
  • Mallat, Stéphane (2008), A Wavelet Tour of Signal Processing: The Sparse Way (PDF) (3rd ed.), pp. 46–47, ISBN 9780123743701
  • Paley, Raymond E. A. C.; Wiener, Norbert (1934). Fourier Transforms in the Complex Domain. Providence, RI: American Mathematical Soc. ISBN 978-0-8218-1019-4. {{cite book}}: ISBN / Date incompatibility (help)
  • Young, Robert M. (2001). An Introduction to Non-Harmonic Fourier Series, Revised Edition, 93. Academic Press. ISBN 978-0-12-772955-8.

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