應缪樹鑫教授邀請，蘭州大學鄭兵教授将來我院作學術報告。
報告題目：Artificial neural network model for some matrix computation problems
報告摘要：In recent years, the artificial neural networks have been deeply studied and investigated with the rapid development of artificial intelligence. As the powerful tools, various neural network algorithms have been designed to efficiently solve many time-varying (or time-invarying) mathematical problems widely arising from robots, space system, signal processing, and automatic control field etc. due to their parallel processing nature and easy implementation in the VLSI system. The aim of this talk is to briefly introduce a gradient-based neural network (GNN, one kind of RNN) for some static-matrix computation problems and another kind of recurrent neural network (called Zhang or zeroing neural network, ZNN) for solving time-varying matrix computation problems. These two neural network models are usually designed as the form of systems of ordinary differential equations with the initial conditions based on the derivative of the associated error function. The design and analysis of these two neural networks can be extended to more types of mathematical problems.
報告時間：2023年02月19日10:00
報告地點：教學9号樓B區311會議室
邀 請 人：缪樹鑫 教授，孟令勝 副教授
屆時歡迎廣大師生參與交流！
報告人簡介
鄭兵，蘭州大學77779193永利教授，博士生導師。長期從事數值代數、神經網絡算法的研究工作，負責承擔國家自然科學基金面上項目、教育部外國專家重點項目、甘肅省自然科學基金項目等10餘項。多次應邀赴美國、日本、西班牙、俄羅斯、印度以及香港、澳門等國家和地區參加學術會議并做學術報告，并先後在印度統計研究所新德裡中心和美國Emory大學數學與計算機系做訪問學者。迄今已在SIAM J. Matrix Anal. Appl., J. Math. Anal. Appl., J. Optim. Theory Appl., Linear Algebra Appl., J. Multivariate Anal., Adv. Comput. Math., IEEE Trans. Neural Network Learn. Syst.,IEEE Trans. Fuzzy Syst., Automatica等國内外著名刊物上發表論文100餘篇。2005年榮獲甘肅省第十二屆高校青年老師成才獎。
甘肅省數學與統計學基礎學科研究中心
77779193永利
