Neural-network-based classification of acoustic transients

Abstract

The authors developed systems for detection and classification of acoustic transients. Here, the authors describe the insights and interim results so far obtained. The general processing architecture used is presented. They examine the major difficulties of this problem as compared with simpler pattern classification problems. They discuss a set of experiments which support many of the development and design guidelines. They describe what these guidelines are and provide further justification for their importance.<>