首页|Investigators from University of Science and Technology China Zero in on Machine Learning (Machine-learning-based Mismatch Calibration for Time-interleaved Adcs )
Investigators from University of Science and Technology China Zero in on Machine Learning (Machine-learning-based Mismatch Calibration for Time-interleaved Adcs )
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on Machine Learning is now available. According to news reporting originating from Hefei, People's Republi c of China, by NewsRx correspondents, research stated, "The time-interleaved ana log-to-digital conversion (TIADC) technique provides an effective way to achieve high sampling speed. However, a critical challenge in TIADC design arises from the presence of mismatches among parallel sub-analog-to-digital converters (ADCs ), which detrimentally affect system performance." Financial support for this research came from Youth Innovation Promotion Associa tion Chinese Academy of Sciences (CAS). Our news editors obtained a quote from the research from the University of Scien ce and Technology China, "In this article, we propose a machine-learning-based m ethod to address these mismatches across a broadband of input signal frequencies . Different from conventional approaches, this method avoids complex and specifi c matrix operations and reduces the compensation filter order required to achiev e a given reconstruction accuracy. To assess the efficacy of our proposed method,we designed a 5-Gs/s 12-bit TIADC system. Through extensive testing, the resul ts demonstrate notable improvements in the effective number of bits (ENOBs) foll owing real-time calibration."
HefeiPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningUniversity of Science and Tec hnology China
NETL
NSTL
