ROAST: Rapid Orthogonal Approximate Slepian Transform

12/13/2017
by   Zhihui Zhu, et al.
0

In this paper, we provide a Rapid Orthogonal Approximate Slepian Transform (ROAST) for the discrete vector one obtains when collecting a finite set of uniform samples from a baseband analog signal. The ROAST offers an orthogonal projection which is an approximation to the orthogonal projection onto the leading discrete prolate spheroidal sequence (DPSS) vectors (also known as Slepian basis vectors). As such, the ROAST is guaranteed to accurately and compactly represent not only oversampled bandlimited signals but also the leading DPSS vectors themselves. Moreover, the subspace angle between the ROAST subspace and the corresponding DPSS subspace can be made arbitrarily small. The complexity of computing the representation of a signal using the ROAST is comparable to the FFT, which is much less than the complexity of using the DPSS basis vectors. We also give non-asymptotic results to guarantee that the proposed basis not only provides a very high degree of approximation accuracy in a mean-square error sense for bandlimited sample vectors, but also that it can provide high-quality approximations of all sampled sinusoids within the band of interest.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
07/13/2018

Non-Gaussian Component Analysis using Entropy Methods

Non-Gaussian component analysis (NGCA) is a problem in multidimensional ...
research
01/01/2018

Least Square Error Method Robustness of Computation: What is not usually considered and taught

There are many practical applications based on the Least Square Error (L...
research
02/15/2023

Randomized Orthogonal Projection Methods for Krylov Subspace Solvers

Randomized orthogonal projection methods (ROPMs) can be used to speed up...
research
12/20/2020

Memory Approximate Message Passing

Approximate message passing (AMP) is a low-cost iterative parameter-esti...
research
04/01/2006

Theoretical Properties of Projection Based Multilayer Perceptrons with Functional Inputs

Many real world data are sampled functions. As shown by Functional Data ...
research
10/22/2018

Sparse constrained projection approximation subspace tracking

In this paper we revisit the well-known constrained projection approxima...
research
11/16/2022

Orthogonal Polynomials Quadrature Algorithm (OPQA): A Functional Analytical Approach to Bayesian Inference

In this paper, we present the new Orthogonal Polynomials-Quadrature Algo...

Please sign up or login with your details

Forgot password? Click here to reset