对“可按需寻址传感器网络：面向大规模主动信息采集”的修正

IF 4.3 2区综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Sensors Journal Pub Date : 2023-10-01 DOI:10.1109/JSEN.2023.3303086

Toshiaki Miyazaki;N. Suematsu;D. Baba;P. Li;S. Guo;J. Kitamichi;T. Hayashi;T. Tsukahara

引用次数: 0

摘要

我们之前发表的文章[2]、[3]报道了上述文章[1]的初步结果，但在文章的参考文献部分被错误地遗漏了。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Corrections to “Demand-Addressable Sensor Network: Toward Large-Scale Active Information Acquisition”

Our previously published articles [2] , [3] , which reported preliminary results of the above article [1] , were erroneously left off in the References Section of the article.

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来源期刊

IEEE Sensors Journal 工程技术-工程：电子与电气

CiteScore

7.70

自引率

14.00%

发文量

2058

审稿时长

5.2 months

期刊介绍： The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice