Machine Learning and Fuzzy Logic in Electronics: Applying Intelligence in Practice

被引：6

作者：

Ivanova, Malinka ^{[1
]}

Petkova, Petya ^{[2
]}

Petkov, Nikolay ^{[2
]}

机构：

[1] Tech Univ Sofia, Fac Appl Math & Informat, Sofia 1000, Bulgaria

[2] Tech Univ Sofia, Coll Energy & Elect, Sofia 1000, Bulgaria

来源：

ELECTRONICS | 2021年 / 10卷 / 22期

关键词：

electronics; machine learning; fuzzy logic; neural networks; intelligent devises; sensors; Internet of Things; robotics; ALGORITHMS; NETWORKS; DESIGN; MODEL;

D O I：

10.3390/electronics10222878

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The paper presents an analysis and summary of the current research state concerning the application of machine learning and fuzzy logic for solving problems in electronics. The investigated domain is conceptualized with aim the achievements, trending topics and future research directions to be outlined. The applied research methodology includes a bibliographic approach in combination with a detailed examination of 66 selected papers. The findings reveal the gradually increasing interest over the last 10 years in the machine learning and fuzzy logic techniques for modeling, implementing and improving different hardware-based intelligent systems.

引用

页数：29

共 81 条

[1] Communication-Efficient Tracking of Unknown, Spatially Correlated Signals in Ad-Hoc Wireless Sensor Networks: Two Machine Learning Approaches [J].