Programming TypeScript: Making Your JavaScript Applications Scale (ePUB) (Publication Date: 2019-05-18)

Deep learning and image processing are two areas of great interest to academics and industry professionals alike. The areas of application of these two disciplines range widely, encompassing fields such as medicine, robotics, and security and surveillance. The aim of this book, Deep Learning for Image Processing Applications, is to offer concepts from these two areas in the same platform, and the book brings together the shared ideas of professionals from academia and research about problems and solutions relating to the multifaceted aspects of the two disciplines. The first chapter provides an introduction to deep learning, and serves as the basis for much of what follows in the subsequent chapters, which cover subjects including: the application of deep neural networks for image classification; hand gesture recognition in robotics; deep learning techniques for image retrieval; disease detection using deep learning techniques; and the comparative analysis of deep data and big data. The book will be of interest to all those whose work involves the use of deep learning and image processing techniques.

An easy introduction to Computational Fluid Dynamics. No prior knowledge of CFD is necessary. Covers the basics - grid generation, numerics, incompressible flow and supersonic flow. Motivates the reader with many examples.

设计数据敏感型应用，对多种存储组件进行分析，可以用于存储组件的技术选型，深入理解各种存储组件的优劣：Data-intensive applications are pushing the boundaries of what is possible by making use of these technological developments. We call an application data-intensive if data is its primary challenge—the quantity of data, the complexity of data, or the speed at Preface Preface | xiii which it is changing—as opposed to compute-intensive, where CPU cycles are the bottleneck. The tools and technologies that help data-intensive applications store and process data have been rapidly adapting to these changes. New types of database systems (“NoSQL”) have been getting lots of attention, but message queues, caches, search indexes, frameworks for batch and stream processing, and related technologies are very important too. Many applications use some combination of these.

通信系统算法介绍 可在开发通信系统时作为参考书 比较基础

Time Series Analysis With Applications in R (Springer)

这是一本由Sen M. Kuo, Bob H. Lee, Wenshun Tian等编写的实时数字信号处理，其中包括了信号处理的基本概念外，还有应用，例如有以下几章：8 - Digital Signal Generators，9 - Dual-Tone Multi-Frequency Detection，10 - Adaptive Echo Cancellation，11 - Speech Coding Techniques，12 - Speech Enhancement Techniques，13 - Audio Signal Processing，14 - Channel Coding Techniques等。

张量分析与力学应用，Tensor Analysis With Applications in Mechanics，资源来自互联网

高清PDF电子书， 关于卡尔曼滤波和小波的，经典书籍，第四版了 Kalman filtering is an optimal state estimation process applied to a dynamic system that involves random perturbations. More precisely, the Kalman filter gives a linear, unbiased, and minimum error variance recursive algorithm to optimally estimate the unknown state of a dynamic system from noisy data taken at discrete real-time. It has been widely used in many areas of industrial and government applications such as video and laser tracking systems, satellite navigation, ballistic missile trajectory estimation, radar, and fire control. With the recent development of high-speed computers, the Kalman filter has become more useful even for very complicated real-time applications. In spite of its importance, the mathematical theory of Kalman filtering and its implications are not well understood even among many applied mathematicians and engineers. In fact, most practitioners are just told what the filtering algorithms are without knowing why they work so well. One of the main objectives of this text is to disclose this mystery by presenting a fairly thorough discussion of its mathe- matical theory and applications to various elementary real-time problems

最近热门研究方向一本难得的Plasmonics 的书，英文原版PDF，可以批注。由浅入深，特别适于初学者和研究人员参考。