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Asynchronous data-driven classification of weapon systems
2009
Measurement science and technology
This paper addresses real-time weapon classification by analysis of asynchronous acoustic data, collected from microphones on a sensor network. The weapon classification algorithm consists of two parts: (i) feature extraction from time-series data using Symbolic Dynamic Filtering (SDF), and (ii) pattern classification based on the extracted features using Language Measure (LM) and Support Vector Machine (SVM). The proposed algorithm has been tested on field data, generated by firing of two
doi:10.1088/0957-0233/20/12/123001
fatcat:xgqhi6pcvbgbjizkn62aen7awe