Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/88592
Title: Efficient capacitive touch sensing using structured matrices
Authors: Akhtar, Humza
Kakarala, Ramakrishna
Keywords: DRNTU::Engineering::Computer science and engineering
Capacitive Touch
Compressive Sampling
Issue Date: 2015
Source: Akhtar, H., & Kakarala, R. (2015). Efficient capacitive touch sensing using structured matrices. Proceedings of SPIE - Computational Imaging XIII, 9401, 94010O-. doi:10.1117/12.2075635
Abstract: Compressive sensing is a technique used in signal processing applications to reduce sampling time. This paper talks about an efficient sampling framework based on compressive sensing for capacitive touch technology. We aim to minimize the number of measurements required during capacitance touch sensing process and in order to achieve this, we use structured matrices which can be used as a driving sensing framework for a touch controller. The novel contribution of this research is that we have modelled our recovery algorithm according to the structure of our sampling matrix, thus making it extremely efficient and simple to implement in a practical application. In this paper, we exploit the structure of the sensing matrix and conduct experiments to test the robustness of our proposed algorithm. Calculations of the floating point multiplication operations for the reconstruction algorithm and sensing matrix have also been looked into detail.
URI: https://hdl.handle.net/10356/88592
http://hdl.handle.net/10220/46951
DOI: http://dx.doi.org/10.1117/12.2075635
Rights: © 2015 Society of Photo-optical Instrumentation Engineers (SPIE). This paper was published in Proceedings of SPIE - Computational Imaging XIII and is made available as an electronic reprint (preprint) with permission of Society of Photo-optical Instrumentation Engineers (SPIE). The published version is available at: [http://dx.doi.org/10.1117/12.2075635]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EOS Conference Papers

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