首页|Reports Summarize Machine Learning Study Results from Southeast University (Know ledge-guided and Machine-learning-assisted Synthesis for Series-fed Microstrip A ntenna Arrays Using Base Element Modeling)
Reports Summarize Machine Learning Study Results from Southeast University (Know ledge-guided and Machine-learning-assisted Synthesis for Series-fed Microstrip A ntenna Arrays Using Base Element Modeling)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Current study results on Machine Learn ing have been published. According to newsoriginating from Nanjing, People’s Re public of China, by NewsRx correspondents, research stated, “Thecomplexity of t he series-fed microstrip antenna array (SFMAA) synthesis problem increases rapid ly withincreasing element number. When dealing with complex practical SFMAA syn thesis problems, conventionalideal antenna-based and electromagnetic (EM) full- wave simulation-based methods are trapped inperformance degradation and time-co nsuming iteratively ‘cut-and-try’ processes.”
NanjingPeople’s Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine LearningSoutheast University
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