Multi-channel Time Encoding for Improved Reconstruction of Bandlimited Signals

Co-authors

Karen Adam and Martin Vetterli.


Downloads

Full text: View at publisher, Infoscience.
Cite: Bibtex.
Code: Infoscience.


Abstract

Traditional sampling involves encoding a signal through (time, value)-pairs. In contrast, time encoding machines (TEMs) characterize a signal by recording time points which depend on the integral of the signal over time. We study multi-channel TEMs where channels have shifted values for their integrators. We show that M channels can enable recovery of bandlimited signals with

Sampling at unknown locations: uniqueness and reconstruction under constraints

Co-authors

Golnoosh Elhami, Michalina Pacholska, Benjamín Béjar Haro and Martin Vetterli.


Downloads

Full text: View at publisher, Infoscience.
Cite: Bibtex.
Code: Infoscience.


Abstract

Traditional sampling results assume that the sample locations are known. Motivated by simultaneous localization and mapping (SLAM) and structure from motion (SfM), we investigate sampling at unknown locations. Without further constraints, the problem is often hopeless. For example, we recently showed that, for polynomial

Sampling and Exact Reconstruction of Pulses with Variable Width

Co-authors

Gilles Baechler, Loïc Baboulaz and Martin Vetterli.


Downloads

Full text: View at publisher, Infoscience.
Cite: Bibtex.
Code: Infoscience.


Abstract

Recent sampling results enable the reconstruction of signals composed of streams of fixed-shaped pulses. These results have found applications in topics as varied as channel estimation, biomedical imaging and radio astronomy. However, in many real signals, the pulse shapes vary throughout the signal. In this paper, we

Site Footer