A Novel Approach to Signal Detection of Sensor Array Units Using 5-3-1 Rule Based Matched Filter Algorithm with Intelligent Identifiers
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Copyright: © 2020 Mahmoud Z. Iskandarani. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
A novel approach to signal detection and identification was developed and tested. The new algorithm was based on provision of tagging a Matched Filter (MF) with identifiers to recognize the source signal with and without noise, so that classification can be carried out. The algorithm was applied successfully to chemical Sensor Array Units (SAU). Problem statement: Signals obtained from chemical sensors were sometimes contaminated with noise. Detection of known signals from noisy surroundings was critical in the field of sensors and their applications. Approach: Six chemical sensor array units were tested at different gas concentrations. The testing was carried out under normal conditions and with the presence of noise. The developed algorithm was then applied to detect, identify and classify the results. Results: The 5-3-1 algorithm produced symmetrical arrays with the source signal identifiers at the corners. The symmetry allowed the use of one-third of the produced data for identification, saving processing time and memory storage. Conclusion: The obtained data also proved that gap separation between conducting electrodes to inversely affect device conductance, with different gap widths affected similarly with temperature change per constant deposited film thickness. Also, each device conductance increased in response to increase in applied gas concentration.
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- Signal detection
- matched filtering