This book is an outgrowth of a course developed at Stanford University over the past five years. It is suitable as a self-contained textbook for second-level undergraduates or for first-level graduate students in almost every field that employs quantitative methods. As prerequisites, it is assumed that the student may have had a first course in differential equations and a first course in linear algebra or matrix analysis. These two subjects, however, are reviewed in Chapters 2 and 3, insofar as they are required for later developments.
标签： Introduction_to_Dynamic_Systems
上传时间： 2020-06-10
上传用户：shancjb
Despite the development of a now vast body of knowledge known as modern control theory, and despite some spectacular applications of this theory to practical situations, it is quite clear that much of the theory has yet to find application, and many practical control problems have yet to find a theory which will successfully deal with them. No book of course can remedy the situation at this time. But the aim of this book is to construct one of many bridges that are still required for the student and practicing control engineer between the familiar classical control results and those of modern control theory.
上传时间： 2020-06-10
上传用户：shancjb
Despite the development of a now vast body of knowledge known as modern control theory, and despite some spectacular applications of this theory to practical situations, it is quite clear that some of the theory has yet to find application, and many practical control problems have yet to find a theory that will successfully deal with them. No one book, of course, can remedy the situation. The aim of this book is to construct bridges that are still required for the student and practicing control engineer between the familiar classical control results and those of modern control theory.
标签： Quadratic Optimal Control Methods Linear
上传时间： 2020-06-10
上传用户：shancjb
Machine learning is a broad and fascinating field. Even today, machine learning technology runs a substantial part of your life, often without you knowing it. Any plausible approach to artifi- cial intelligence must involve learning, at some level, if for no other reason than it’s hard to call a system intelligent if it cannot learn. Machine learning is also fascinating in its own right for the philo- sophical questions it raises about what it means to learn and succeed at tasks.
标签： Learning Machine Course in
上传时间： 2020-06-10
上传用户：shancjb
It all started rather innocuously. I walked into Dr GT Murthy’s office one fine day, andchanged my life. “Doc” was then the General Manager, Central R&D, of a very largeelectrical company headquartered in Bombay. In his new state-of-the-art electronics center,he had hand-picked some of India’s best engineers (over a hundred already) ever assembledunder one roof. Luckily, he too was originally a Physicist, and that certainly helped me gainsome empathy. Nowadays he is in retirement, but I will always remember him as athoroughly fair, honest and facts-oriented person, who led by example. There were severalthings I absorbed from him that are very much part of my basic engineering persona today.You can certainly look upon this book as an extension of what Doc started many years agoin India … because that’s what it really is! I certainly wouldn’t be here today if I hadn’t metDoc. And in fact, several of the brash, high-flying managers I’ve met in recent years,desperately need some sort of crash course in technology and human values from Doc!
标签： 开关电源
上传时间： 2021-11-23
上传用户：
斯坦福大学-深度学习基础教程.pdfUFLDL教程 From Ufldl 说明：本教程将阐述无监督特征学习和深入学习的主要观点。通过学习，你也将实现多个功能 学习/深度学习算法，能看到它们为你工作，并学习如何应用/适应这些想法到新问题上。 本教程假定机器学习的基本知识（特别是熟悉的监督学习，逻辑回归，梯度下降的想法），如果 你不熟悉这些想法，我们建议你去这里 机器学习课程 (http://openclassroom.stanford.edu/MainFolder/CoursePage.php? course=MachineLearning) ，并先完成第II，III，IV章（到逻辑回归）。 稀疏自编码器 神经网络 反向传导算法 梯度检验与高级优化 自编码算法与稀疏性 可视化自编码器训练结果 稀疏自编码器符号一览表 Exercise:Sparse Autoencoder 矢量化编程实现 矢量化编程 逻辑回归的向量化实现样例 神经网络向量化 Exercise:Vectorization
标签： 深度学习
上传时间： 2022-03-27
上传用户：kingwide
