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Algebraic theory of signal processing (SMART)


Algebraic theory of signal processing (SMART) as an area was started by Markus Püschel, whose goal is to formulate an algebraic framework for signal processing. Our current work focuses on understanding and formulating such a framework for filter banks and multiresolution transforms.

 

Overview


Sponsors

Some of this material is based upon work supported by the National Science Foundation under 310941 and 9988296 and the PA State Tobacco Settlement, Kamlet-Smith Bioinformatics Grant.

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the sponsor(s).

Collaborators

Markus Püschel, Aliaksei Sandryhaila

Research Corner

Sampling

Multiresolution analysis

Filter banks and wavelets

Frames

Teaching Corner

Recent publications

Recent talks

Links

SMART site

 

Sampling


Sampling theorems for trigonometric transforms

One way of deriving the discrete Fourier transform (DFT) is by equispaced sampling of periodic signals or signals on a circle.  In this paper, we show that an analogous derivation can be used to obtain the DCT (type 2). To achieve this goal, we replace the circle by a line graph with symmetric boundary conditions, and define signal space, filter space, and filtering operation appropriately.  Further, we derive the corresponding sampling theorem including the proper notions of ``bandlimited'' and ``sinc function.''  The results show that, in a rigorous sense, the DCT is closely related to the DFT, and can be introduced without concepts from statistical signal processing as is the current practice.

J. Kovačević and M. Püschel, ''Sampling theorem associated with the discrete cosine transform'', Proc. IEEE Int. Conf. Acoust., Speech, and Signal Proc., Toulouse, France, May 2006.

 

Multiresolution analysis


Under construction

Filter banks and wavelets


Under construction

Frames


Frames with maximal robustness to erasures

Motivated by the use of frames for robust transmission over the Internet, we present a first systematic construction of real tight frames with maximum robustness to erasures. We approach the problem in steps: we first construct maximally robust frames by using polynomial transforms. We then add tightness as an additional property with the help of orthogonal polynomials.  Finally, we impose the last requirement of equal norm and construct, to our best knowledge, the first real, tight, equal-norm frames maximally robust to erasures.

M. Püschel and J. Kovačević, ''Real, tight frames with maximal robustness to erasures'', Proc. Data Compr. Conf., Snowbird, UT, March 2005, pp. 63-72.

 

Recent publications


J. Kovačević and M. Püschel, ''Sampling theorem associated with the discrete cosine transform'', Proc. IEEE Int. Conf. Acoust., Speech, and Signal Proc., Toulouse, France, May 2006.

M. Püschel and J. Kovačević, ''Real, tight frames with maximal robustness to erasures'', Proc. Data Compr. Conf., Snowbird, UT, March 2005, pp. 63-72.

 

Recent talks


Sampling theorem associated with the discrete cosine transform

Real, tight frames with maximal robustness to erasures