Robotics & Machine Learning Daily News2024,Issue(Dec.2) :87-88.

Study Results from Al-Farabi Kazakh National University Update Understanding of Machine Learning (Novel Filtering and Regeneration Technique With Statistical Fe ature Extraction and Machine Learning for Automatic Modulation Classification)

Al-Farabi哈萨克国立大学的研究结果更新了对机器学习的理解(具有统计特征提取和机器学习的新滤波和再生技术用于自动调制分类)

Robotics & Machine Learning Daily News2024,Issue(Dec.2) :87-88.

Study Results from Al-Farabi Kazakh National University Update Understanding of Machine Learning (Novel Filtering and Regeneration Technique With Statistical Fe ature Extraction and Machine Learning for Automatic Modulation Classification)

Al-Farabi哈萨克国立大学的研究结果更新了对机器学习的理解(具有统计特征提取和机器学习的新滤波和再生技术用于自动调制分类)

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摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-调查人员发布马学习新报告。根据新闻报道来自哈萨克斯坦阿拉木图,由NewsRx记者报道,研究称,“自动调制”在未知源信号的处理阶段,(AMC)的分类起着至关重要的作用监控电波。提出了一种基于机器学习(ML)的AMC方法星座图、分布测试函数和高阶累积量(HOCs)及新滤波和再生技术。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators publish new report on Ma chine Learning. According to news reportingoriginating from Alma Ata, Kazakhsta n, by NewsRx correspondents, research stated, “Automatic modulationclassificati on (AMC) plays a crucial role in the stages of processing signals from unknown s ourcesand monitoring the airwaves. This paper presents an AMC method based on m achine learning (ML) usingconstellation diagrams, distribution test function an d high-order cumulants (HOCs) and novel filteringand regeneration technique.”

Key words

Alma Ata/Kazakhstan/Asia/Cyborgs/Eme rging Technologies/Machine Learning/Al-Farabi Kazakh National University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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