This study presents a comprehensive overview of the classification of time signals over a variety of objects. Signals were initially processed using the Hilbert-Huang transform, followed by supervised machine learning and deep learning to classify objects. Multilayer Perceptron (MLP) and Support Vector Machines (SVM) were used for sound discrimination. The result is a program that effectively detects and classifies time signals as "Object 1" or "Not Object 1" (i.e., Object #2 and Object 3). |
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