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SIGNAL PROCESSING AND MACHINE LEARNING FOR INNOVATION ENGINE IBD

OMNIABOOKS - OMNIASCIENCE
10 / 2025
9788412968606
Inglés

Sinopse

This book presents recent advances in signal processing and artificial neural network (ANN) applications aimed at driving innovation in engineering. The proposed developments constitute advanced IT solutions for research, data access, and knowledge management, primarily built upon Internet of Things (IoT)-assisted architectures. The techniques described integrate signal processing with wireless neural network implementations. Several signal processing, feature selection, and feature extraction approaches are explored, including the use of bandpass filters combined with numerical derivatives, the Hilbert transform, adaptive thresholding, moving average filters, autocorrelation functions, wavelet transforms, and the HilbertHuang transform. For feature selection, methods such as feature normalization and the False Nearest Neighbor (FNN) technique are examined, while principal component analysis (PCA) is applied for feature extraction. The book also presents real-time tests to assess Io

PVP
24,90