Toward real-time kernel density estimate display for instrumentation
Measurement Research Laboratory, Agilent Technologies, 561 Keystone Ave. MS 434, Reno, NV 89503 USA
IEEE Instrumentation and Measurement Technology Conference (I2MTC), 2011
@inproceedings{barford2011toward,
title={Toward real-time kernel density estimate display for instrumentation},
author={Barford, L. and Gibbs, I. and Kelley, R.},
booktitle={Instrumentation and Measurement Technology Conference (I2MTC), 2011 IEEE},
pages={1–6},
year={2011},
organization={IEEE}
}
Histograms are commonly used in instrumentation to produce a visual representation of the probability density of a random signal from repeated measurements. However, histograms have a number of shortcomings as a method of data visualization. We propose using kernel density estimation as a replacement for histograms in instrumentation. Kernel density estimation has a number of advantages as a means of visualizing the probability density of a waveform or derived measurement. However, kernel density estimates have been considered too computationally burdensome for inclusion in instruments and virtual instruments. In this paper, we demonstrate that a graphics processing unit (GPU) can be used to compute and display kernel density estimates of actual measured data at a full video rate.
July 29, 2011 by hgpu
