Guest Editorial Special Section on Signal Processing and Machine Learning in Intelligent Instrumentation, IEEE Open Journal of Instrumentation and Measurement

There has been tremendous interest in the development and deployment of Signal Processing and Machine Learning algorithms for almost all areas of instrumentation and measurement systems, starting from power systems, transportation, biomedical and healthcare, industrial measurements and automation, r...

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Bibliographic Details
Main Authors: Anirban Mukherjee, Rajarshi Gupta, Amitava Chatterjee
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Open Journal of Instrumentation and Measurement
Online Access:https://ieeexplore.ieee.org/document/10352322/
Description
Summary:There has been tremendous interest in the development and deployment of Signal Processing and Machine Learning algorithms for almost all areas of instrumentation and measurement systems, starting from power systems, transportation, biomedical and healthcare, industrial measurements and automation, robotics and mechatronics, smart infrastructure, and facility management to aerospace and navigation. Their combination, signal processing and machine learning, is expected to dominate the next decade industrial developments. In order to embed the “intelligence” into the measurement, signal processing has been one of the ubiquitous techniques for quite some time. Machine learning methods make these intelligent methods “experienced.” Because machine learning has been around in recent years, signal processing software–hardware systems equipped with machine learning are relatively mature. In this Special Section, a call for paper included (but were not limited to) the following areas.
ISSN:2768-7236