Data Driven Sampling of Oscillating Signals

Data driven sampling of oscillating signals

The reduction of the number of samples is a key issue in signal processing for mobile applications. We investigate the link between the smoothness properties of a signal and the number of samples that can be obtained through a level crossing sampling procedure. The algorithm is analyzed and an upper bound of the number of samples is obtained in the worst case. The theoretical results are illust...

Scene Parsing by Data Driven Cluster Sampling

This paper presents a data-driven cluster sampling framework for parsing scene images into generic regions (such as the sky, mountain and water) and objects (such as cows, horses and cars). We adopt generative models for both generic regions and objects, thus their likelihood probabilities are comparable and are learned under a common information projection principle. The inference algorithm fo...

The use of sampling techniques in dynamic data driven simulations ∗

In this paper we discuss some numerical procedures involved in dynamic data driven simulations (DDDAS). The main objective of this paper is the recovery of the initial data as well as the media properties based on dynamic data. We consider the contaminant transport in porous media with a number of sensors placed at some locations. Based on measured data we propose to recover the permeability fi...

Seismic Data Up-sampling beyond Aliasing Using Polynomial Phase Signals

Skyrmion motion driven by oscillating magnetic field

The one-dimensional magnetic skyrmion motion induced by an electric current has attracted much interest because of its application potential in next-generation magnetic memory devices. Recently, the unidirectional motion of large (20 μm in diameter) magnetic bubbles with two-dimensional skyrmion topology, driven by an oscillating magnetic field, has also been demonstrated. For application in hi...