Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

A Memristor-Based Compressive Sampling Encoder with Dynamic Rate Control for Low-Power Video Streaming

A Memristor-Based Compressive Sampling Encoder with Dynamic Rate Control for Low-Power Video... Image sensors are widely used in various applications. With the increasing requirement for high resolutions and frame rates, power consumption has become a critical issue, which limits the use of image sensors in mobile devices and IoT applications. Compressive sensing (CS) techniques can achieve a sub-Nyquist sampling rate to reduce the power consumption in hardware circuits. Currently, most compressive measurements are implemented in digital CMOS circuits, leading to high hardware complexity and power consumption, as well as the limited sampling speed. Furthermore, CS applications with large image sizes are usually based on block-wise methods, which require real-time rate controls during practical operations. In this article, we propose a memristor-based CS encoder that can be integrated with conventional image sensors to achieve high performance with low power consumption and hardware overheads. A self-adaptive compressing rate control mechanism is also devised to maximize the performance of the proposed technique. Simulation results of wireless video streaming demonstrate the advantages of the proposed technique. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Journal on Emerging Technologies in Computing Systems (JETC) Association for Computing Machinery

A Memristor-Based Compressive Sampling Encoder with Dynamic Rate Control for Low-Power Video Streaming

Download PDF
16 pages

Loading next page...
 
/lp/association-for-computing-machinery/a-memristor-based-compressive-sampling-encoder-with-dynamic-rate-2OGX0rO8n9

References (48)

Publisher
Association for Computing Machinery
Copyright
Copyright © 2020 ACM
ISSN
1550-4832
eISSN
1550-4840
DOI
10.1145/3365836
Publisher site
See Article on Publisher Site

Abstract

Image sensors are widely used in various applications. With the increasing requirement for high resolutions and frame rates, power consumption has become a critical issue, which limits the use of image sensors in mobile devices and IoT applications. Compressive sensing (CS) techniques can achieve a sub-Nyquist sampling rate to reduce the power consumption in hardware circuits. Currently, most compressive measurements are implemented in digital CMOS circuits, leading to high hardware complexity and power consumption, as well as the limited sampling speed. Furthermore, CS applications with large image sizes are usually based on block-wise methods, which require real-time rate controls during practical operations. In this article, we propose a memristor-based CS encoder that can be integrated with conventional image sensors to achieve high performance with low power consumption and hardware overheads. A self-adaptive compressing rate control mechanism is also devised to maximize the performance of the proposed technique. Simulation results of wireless video streaming demonstrate the advantages of the proposed technique.

Journal

ACM Journal on Emerging Technologies in Computing Systems (JETC) – Association for Computing Machinery

Published: Jan 28, 2020

Keywords: Memristor

There are no references for this article.