| 摘要 |
An acoustic event classifier uses particle swarm optimization (PSO) to perform a flexible time correlation of a sensed acoustic signature to reference acoustic signatures in a multi-dimensional parameter space. The classifier may fuse the acoustic signatures from multiple acoustic sensors to form the sensed acoustic signature. The approach is generally applicable to classify all types of acoustic events but is particularly well-suited to classify “explosive” events such as gun shots, mortar blasts, improvised explosive device blasts etc. that produce an acoustic signature having a shock wave component that is periodic and non-linear.
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