Intended Audience The intended audience is upper level undergraduate students, graduate students and researchers in computer graphics and vision and related areas. If you are a believer of the saying “A mathematician is a blind man in a dark room looking for a black cat which is not there”, probably this book is not for you. You should consider returning the book and getting a refund. If you have been looking for a book with a concise account of a certain topic but only was frustrated because the books for mathematics majors have too many details than you needed, I hope this is the book you have been looking for.

内容为为中文影印版，还算比较清楚； 资源来自于CSDN，为了方便使用，添加了完整书签；

Digital Signal Processing: Principles, Algorithms and Applications (3rd Edition)Part 1

DSP入门经典教材，djvu格式，目录制作精良，供参考

1.简介 2.Jaya优化算法及其变体 再也算法及其变体的上3.应用受约束和不受约束的基准函数 4.使用Jaya算法及其变体对换热器进行单目标和多目标设计优化 5.使用Jaya算法及其变体对热管和散热器的单目标和多目标设计优化6.使用Jaya算法及其变体对 冰蓄热系统进行多目标设计优化 7.传统的单目标和多目标优化Jaya算法及其变体的现代和现代加工工艺 8.使用Jaya算法及其变体的纳米精加工的 单目标和多目标优化9.使用Jaya算法及其变体的铸造工艺的单目标和多目标优化 10。 Jaya算法及其修改版本在工程科学领域中的应用

Electric Motors and Drives Fundamentals, Types and Applications Fifth Edition Austin Hughes Bill Drury Abstract Non-specialist readers wishing to learn the essence of how and why motors work will find answers in this chapter. We discuss how to quantify magnetic effects, explain how force and torque are generated, and show that the elegant energy-converting process can be predicted using a simple equivalent circuit. The key factors that underpin the operation of all types of motor emerge, and we conclude by identifying the simple design parameters that determine the relationship between rotor volume and torque.

书籍《Computational Photography: Methods and Applications》 PDF原版。

【源码】matlab程序在动力系统中的应用

线性规划与应用，英文版

This chapter covers the basics of TensorFlow, the deep learning framework. Deep learning does a wonderful job in pattern recognition, especially in the context of images, sound, speech, language, and time-series data. With the help of deep learning, you can classify, predict, cluster, and extract features. Fortunately, in November 2015, Google released TensorFlow, which has been used in most of Google’s products such as Google Search, spam detection, speech recognition, Google Assistant, Google Now, and Google Photos. Explaining the basic components of TensorFlow is the aim of this chapter.