龚升 [简明微积分(第四版)] 带书签版本 高等教育出版社

江西财经大学《微积分》期末考试试卷（含答案）

清华大学《微积分》期末复习资料（含答案）

厦门大学《多元微积分》期中期末复习资料

厦门大学《一元微积分A》期末考试试卷（含答案）

高等微积分习题解答II

高等微积分习题I.pdf

Fractional-order calculus is about the differentiation and integration of non-integer orders. Fractional calculus (FC) is based on fractional-order thinking (FOT) and has been shown to help us to understand complex systems better, improve the processing of complex signals, enhance the control of complex systems, increase the performance of optimization, and even extend the enabling of the potential for creativity. In this article, the authors discuss the fractional dynamics, FOT and rich fractional stochastic models. First, the use of fractional dynamics in big data analytics for quantifying big data variability stemming from the generation of complex systems is justified. Second, we show why fractional dynamics is needed in machine learning and optimal randomness when asking: “is there a more optimal way to optimize?”. Third, an optimal randomness case study for a stochastic configuration network (SCN) machine-learning method with heavy-tailed distributions is discussed. Finally, views on big data and (physics-informed) machine learning with fractional dynamics for future research are presented with concluding remarks. https://www.mdpi.com/1099-4300/23/3/297/pdf

matlab实现参数方程求导 具体描述见下面网址： https://blog.csdn.net/weixin_43964993/article/details/107863569

这本教材在中国科技大学已经用了十多年，介绍了微分，积分这对矛盾，以简明的的方式介绍微积分