Multi-Acoustic Target classification Using Wireless Sensor Network - Aljaafreh, Ahmad
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Battlefield surveillance, border monitoring, and intelligent traffic system are some of the applications of the classification of ground vehicles based on acoustic signals. Classification of multiple dynamic targets based on time varying continuous signals in WSNs is a big challenge in many of WSNs applications. In this book, I tackled the problem of classification of multiple moving ground vehicles, that are passing through a region monitored by wireless sensors, where the number of these vehicles is evolving with time. This work investigated the problem from three aspects:the first is the…mehr

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Produktbeschreibung
Battlefield surveillance, border monitoring, and intelligent traffic system are some of the applications of the classification of ground vehicles based on acoustic signals. Classification of multiple dynamic targets based on time varying continuous signals in WSNs is a big challenge in many of WSNs applications. In this book, I tackled the problem of classification of multiple moving ground vehicles, that are passing through a region monitored by wireless sensors, where the number of these vehicles is evolving with time. This work investigated the problem from three aspects:the first is the feature extraction, The second is the utilization of the time correlation of the observation, In the third part a collaborative fuzzy dynamic weighted majority voting (CFDWMV) algorithm is developed to fuse all of the local decisions and make decision on targets number.
Autorenporträt
Dr. Ahmad Aljaafreh is an assistant professor at Electrical Engineering Department, Tafila Technical University.