Constructing finite frames of a given spectrum and set of lengths

When constructing finite frames for a given application, the most important consideration is the spectrum of the frame operator. Indeed, the minimum and maximum eigenvalues of the frame operator are the optimal frame bounds, and the frame is tight precisely when this spectrum is constant. Often, the second-most important design consideration is the lengths of frame vectors: Gabor, wavelet, equiangular and Grassmannian frames are all special cases of equal norm frames, and unit norm tight frame-based encoding is known to be optimally robust against additive noise and erasures. We consider the problem of constructing frames whose frame operator has a given spectrum and whose vectors have prescribed lengths. For a given spectrum and set of lengths, the existence of such frames is characterized by the Schur-Horn Theorem---they exist if and only if the spectrum majorizes the squared lengths---the classical proof of which is nonconstructive. Certain construction methods, such as harmonic frames and spectral tetris, are known in the special case of unit norm tight frames, but even these provide but a few examples from the manifold of all such frames, the dimension of which is known and nontrivial. In this paper, we provide a new method for explicitly constructing any and all frames whose frame operator has a prescribed spectrum and whose vectors have prescribed lengths. The method itself has two parts. In the first part, one chooses eigensteps---a sequence of interlacing spectra---that transform the trivial spectrum into the desired one. The second part is to explicitly compute the frame vectors in terms of these eigensteps; though nontrivial, this process is nevertheless straightforward enough to be implemented by hand, involving only arithmetic, square roots and matrix multiplication.

[1]  Nate Strawn,et al.  Finite Frame Varieties: Nonsingular Points, Tangent Spaces, and Explicit Local Parameterizations , 2011 .

[2]  Peter G. Casazza,et al.  Constructing tight fusion frames , 2011 .

[3]  Vivek K Goyal Quantized Overcomplete Expansions : Analysis , Synthesis and Algorithms , 1995 .

[4]  J. Kovacevic,et al.  Life Beyond Bases: The Advent of Frames (Part II) , 2007, IEEE Signal Processing Magazine.

[5]  Robert W. Heath,et al.  Generalized Finite Algorithms for Constructing Hermitian Matrices with Prescribed Diagonal and Spectrum , 2005, SIAM J. Matrix Anal. Appl..

[6]  Shayne Waldron,et al.  Generalized Welch bound equality sequences are tight fram , 2003, IEEE Trans. Inf. Theory.

[7]  Keri Kornelson,et al.  Ellipsoidal tight frames and projection decompositions of operators , 2003 .

[8]  Moody T. Chu,et al.  Constructing a Hermitian Matrix from Its Diagonal Entries and Eigenvalues , 1995, SIAM J. Matrix Anal. Appl..

[9]  Nate Strawn,et al.  Manifold structure of spaces of spherical tight frames , 2003, math/0307367.

[10]  John J. Benedetto,et al.  Finite Normalized Tight Frames , 2003, Adv. Comput. Math..

[11]  V. Paulsen,et al.  Optimal frames for erasures , 2004 .

[12]  Peter G. Casazza,et al.  Auto-tuning unit norm frames , 2010, 1009.5562.

[13]  Charles R. Johnson,et al.  Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.

[14]  Peter G. Casazza,et al.  Equal-Norm Tight Frames with Erasures , 2003, Adv. Comput. Math..

[15]  Robert W. Heath,et al.  Designing structured tight frames via an alternating projection method , 2005, IEEE Transactions on Information Theory.

[16]  Vivek K Goyal,et al.  Quantized Frame Expansions with Erasures , 2001 .

[17]  Bernhard G. Bodmann,et al.  The road to equal-norm Parseval frames , 2010 .

[18]  N. T. Thao,et al.  QUANTIZED OVER COMPLETE EXPANSIONS IN RN: ANALYSIS , 1998 .

[19]  J. Kovacevic,et al.  Life Beyond Bases: The Advent of Frames (Part I) , 2007, IEEE Signal Processing Magazine.

[20]  Peter G. Casazza,et al.  A Physical Interpretation of Tight Frames , 2006 .

[21]  P. Massey,et al.  TIGHT FRAME COMPLETIONS WITH PRESCRIBED NORMS. , 2006 .

[22]  Chi-Ren Shyu,et al.  Image Analysis for Mapping Immeasurable Phenotypes in Maize [Life Sciences] , 2007, IEEE Signal Processing Magazine.

[23]  A. Horn Doubly Stochastic Matrices and the Diagonal of a Rotation Matrix , 1954 .

[24]  Venkat Anantharam,et al.  Optimal sequences and sum capacity of synchronous CDMA systems , 1999, IEEE Trans. Inf. Theory.

[25]  Lloyd R. Welch,et al.  Lower bounds on the maximum cross correlation of signals (Corresp.) , 1974, IEEE Trans. Inf. Theory.

[26]  P. Massey,et al.  THE SCHUR-HORN THEOREM FOR OPERATORS AND FRAMES WITH PRESCRIBED NORMS AND FRAME OPERATOR. , 2005 .