ICCT 2022 Invited Speaker

Yindong Xiao, University of  Electronic  Science and Technology of China, China
肖寅东, 电子科技大学

Associate Professor Yingdong Xiao, University of Electronic Science and Technology of China. The research direction is network testing and synchronization technology with computer technology as the core platform, high-speed data generation technology, and testing system integration technology (including integrated circuit testing, network equipment testing, etc.). As the person in charge or the main researcher, he has presided over and undertaken 1 Natural Science Foundation project and more than 10 provincial and ministerial research projects. Won the first prize of provincial and ministerial level scientific and technological progress. He has published more than 10 papers in important academic journals at home and abroad, and has been granted more than 10 national invention patents and 2 software copyrights. He is a reviewer for the internationally renowned academic journal "ISA Transaction".

Speech Title: A digital noise signal synthesis method based on a combination of table look-up and transformation
The digital noise signal synthesis method has good scalability and flexibility. The table lookup-based synthesis method stores the noise data that meets the specified distribution in memory by pre-calculation, maps the uniformly distributed random numbers to actual physical addresses as address inputs, and addresses the noise data to be output by the DAC. The transformation-based synthesis method uses the transformation formula to calculate the uniformly distributed random numbers in real time, and the result of the calculation is output by the DAC to generate the noise that matches the specified distribution. However, the hardware storage depth limits the accuracy of the noise distribution output by the look-up table method, and the real-time computation speed limits the output speed of the transformation method. In this paper, we propose a new method for digital noise signal synthesis, which solves the problem that the accuracy of the output distribution of the look-up table method depends on a large storage space and improves the accuracy of the output without adding additional storage space.