Abstract
A novel approach to signal detection and identific ation 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 class ification 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 sen sors and their applications. Approach: Six chemical sensor array units were tested at different gas con centrations. The testing was carried out under norm al conditions and with the presence of noise. The deve loped algorithm was then applied to detect, identif y and classify the results. Results: The 5-3-1 algorithm produced symmetrical arrays with the source signal identifiers at the corners. The symmetry all owed the use of one-third of the produced data for identification, saving processing time and memory s torage. Conclusion: The obtained data also proved that gap separation between conducting electrodes t o inversely affect device conductance, with different gap widths affected similarly with temper ature change per constant deposited film thickness. Also, each device conductance increased in response to increase in applied gas concentration.
Highlights
Noise reduction and elimination is a typical problem in signal processing as well as many applications in the real world
Matched Filtering algorithms are one of the adaptive systems that are widely used in signal applications because of their remarkable ability to extract patterns from surrounding noise, can be applied to many real world problems such as pattern recognition, signal processing, optimization, control and others
Each testing cell formed an array of three multi-gap chemical sensors making an overall array of nine sensing elements per testing cell
Summary
Noise reduction and elimination is a typical problem in signal processing as well as many applications in the real world. Matched filtering is very useful in testing and processing an array of N-sensors so as to constantly check detection conditions of any of the sensors and obtain a numerical and graphical data certifying if that sensor or others are working properly. It operates on the principle of correlating an input array (known valued array) and another array surrounded by noise or interference (unknown valued array).The closest match can be found by allocating the output with the largest correlated value. The resulted Filter is applied to detect and process signals obtained from a chemical sensors array units
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