報(bào)告題目：Two Sides of Noise: Good and Bad

報(bào)告人： 毛學(xué)榮 教授 英國(guó)思克萊德大學(xué)

報(bào)告時(shí)間：2025年7月17日上午8:30-9:30

報(bào)告地點(diǎn)：kaiyun開(kāi)云官方網(wǎng)站犀浦校區(qū)X30456

報(bào)告摘要：One of the important problems in many branches of science and industry, e.g., pandemic, ecology, biology, engineering, finance, social science, is the specification of the stochastic process governing the behaviour of an underlying quantity. We here use the term {\it underlying quantity\/} to describe any interested object whose value is known at present but is liable to change in the future. In this talk we will explain how the ordinary differential equations (ODEs) are not enough to model the underlying stochastic quantity and why stochastic differential equations (SDEs) appear naturally. Several well-known SDE models will be presented including the Nobel prize winning model in finance, stochastic SIS epidemic model, stochastic Lotka-Volterra model in population dynamics. We will then explain how SDE models differ significantly from ODE models and reveal two sides of noise: good and bad. We will highlight how we can make use of noise in various applications including stochastic stabilisation, volatility effect in finance, population explosion suppressed by noise, extinction of infected individuals by noise in epidemic while we will also point out the destabilisation effect of noise.

報(bào)告人簡(jiǎn)介：英國(guó)思克萊德大學(xué)數(shù)學(xué)與統(tǒng)計(jì)系教授、愛(ài)丁堡皇家學(xué)會(huì)（即蘇格蘭皇家學(xué)院）院士、“英國(guó)沃弗森研究功勛獎(jiǎng)”獲得者。他是國(guó)際知名的隨機(jī)穩(wěn)定性和隨機(jī)控制領(lǐng)域的專(zhuān)家，在該領(lǐng)域做出了杰出的貢獻(xiàn)。他擅長(zhǎng)隨機(jī)分析、隨機(jī)系統(tǒng)數(shù)值計(jì)算，在隨機(jī)系統(tǒng)處理方面，提出了系列處理方法與技巧，被廣泛采用。例如，對(duì)噪聲鎮(zhèn)定給出了科學(xué)的理論，被后續(xù)跟蹤者所廣泛推崇；在隨機(jī)人口以及疾病模型理論方面做出了突出的貢獻(xiàn)；在隨機(jī)系統(tǒng)LaSalle原理方面做出了開(kāi)拓性的工作；奠定了隨機(jī)跳變系統(tǒng)理論方面的研究。