智能仪器仪表中的信号处理和机器学习》特约编辑专栏,《IEEE 仪器仪表与测量开放式期刊》(IEEE Open Journal of Instrumentation and Measurement

Anirban Mukherjee;Rajarshi Gupta;Amitava Chatterjee
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引用次数: 0

摘要

从电力系统、交通运输、生物医学和医疗保健、工业测量和自动化、机器人技术和机电一体化、智能基础设施、设施管理到航空航天和导航,几乎所有仪器仪表和测量系统领域都对信号处理和机器学习算法的开发和应用产生了极大的兴趣。它们与信号处理和机器学习的结合有望主导未来十年的工业发展。为了将 "智能 "嵌入测量中,信号处理技术早已成为无处不在的技术之一。机器学习方法让这些智能方法变得 "经验丰富"。由于机器学习是近几年才出现的,因此具备机器学习功能的信号处理软硬件系统已经相对成熟。本特别分会的论文征集包括(但不限于)以下领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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, 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.
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