Abstract: Time series classification is an important task in time series data mining, and has attracted great interests and tremendous efforts during last decades. However, it remains a challenging ...

Abstract: In this monograph, the authors present an introduction to the framework of variational autoencoders (VAEs) that provides a principled method for jointly learning deep latent-variable models ...

Book Abstract: Electrical Engineering Wave Propagation and Scattering in Random Media A volume in the IEEE/OUP Series on Electromagnetic Wave Theory Donald G. Dudley, Series Editor This IEEE Classic ...

Book Abstract: Electrical Engineering/Electromagnetics Waves and Fields in Inhomogeneous Media A Volume in the IEEE Press Series on Electromagnetic Waves Donald G ...

Book Abstract: First published in 1981, Robert S. Elliott's Antenna Theory and Design is one of the most significant works in electromagnetic theory and applications. In its broad-ranging, analytic ...

Book Abstract: Analyzes the dynamic performance of interconnected power systems. * Examines the characteristics of the various components of a power system during normal operating conditions and ...

Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=6731005 ...

Abstract: The detection of anomalies in multisource time-series data is crucial for the efficient operation of the Internet of Things (IoT) devices and large-scale cross-domain systems. Recent methods ...