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Signal Processing and Machine Learning Techniques Towards Various Real-World Applications

Abstract Machine learning (ML) has played an important role in several modern technological innovations and has become an important tool for researchers in various fields of interest. Besides engineering, ML techniques have started to spread across various departments of study, like health-care, medicine, diagnostics, social science, finance, economics etc. These techniques require data to train the algorithms and model a complex system and make predictions based on that model. Due to development of sophisticated sensors it has become easier to collect large volumes of data which is used to make necessary hypotheses using ML. The promising results obtained using ML have opened up new opportunities of research across various departments and this diss... (more)
Created Date 2018
Contributor Dutta, Arindam (Author) / Bliss, Daniel W (Advisor) / Berisha, Visar (Committee member) / Richmond, Christ (Committee member) / Corman, Steven (Committee member) / Arizona State University (Publisher)
Subject Electrical engineering / Biomedical engineering / EEG / Gut-Microbiome / Machine Learning / Signal Processing / Wearables
Type Doctoral Dissertation
Extent 184 pages
Language English
Note Doctoral Dissertation Electrical Engineering 2018
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis