Discrete Signal Processing on Graphs: Sampling Theory

Expository Notes on Signal Processing on Graphs

Graph theory has developed into a useful tool in applied mathematics as many modern data sets are or can be represented as a graph. In these data sets, vertices correspond to different sensors, observations, or data points and edges represent connections, similarities, or correlations among those points. Some immediate applied examples include social network data, electricity networks, and imag...

Discrete Time Signal Processing

Discrete Signal Processing Notes

Algebraic Signal Processing Theory

This paper presents an algebraic theory of linear signal processing. At the core of algebraic signal processing is the concept of a linear signal model defined as a triple (A,M,Φ), where familiar concepts like the filter space and the signal space are cast as an algebra A and a module M, respectively, and Φ generalizes the concept of the z-transform to bijective linear mappings from a vector sp...

Discrete Frequency Warped Wavelets: Theory and Applications - Signal Processing, IEEE Transactions on

In this paper, we extend the definition of dyadic wavelets to include frequency warped wavelets. The new wavelets are generated and the transform computed in discrete-time by alternating the Laguerre transform with perfect reconstruction filterbanks. This scheme provides the unique implementation of orthogonal or biorthogonal warped wavelets by means of rational transfer functions. We show that...