Signals and Systems (信号与系统) Second Edition Oppenheim Solutions 英文原版 本书全面系统地论述了信号与系统分析的基本理论和方法。全书共11章，内容包括：信号与系统、线性时不变系统，周期信号的傅里叶级数表示，连续和离散时间傅里叶变换，信号与系统的时域和频域特性，采样，通信系统，拉普拉斯和z变换以及线性反馈系统。每章都有足够数量的例题和大量精选的习题；并将习题分列为4种栏目，分属3种不同的层次，便于使用。 　　 本书是在第1版基础之上经重新组织，重新改写并作补充而成，除保留原书结构新颖，选材得当，论述严谨，条理清楚等特色外，在某些方面更有所加强，恰似锦上添花，堪称反映信号与系统分析当代水平的一部佳作。 　　 本书可作为通信与电子系统类，自动化类以及全部电类专业信号与系统课程的教材，也可以供任何从事信息获取、转换、传输及处理工作的其它专业研究生，教师和广大科技工作者参考。 part1 地址http://download.csdn.net/source/1220163

Mastering OpenCV 3 - Second Edition by Daniel Lélis Baggio English | 4 May 2017 | ASIN: B01N7G0BKE | 250 Pages | AZW3 | 4.82 MB Key Features Updated for OpenCV 3, this book covers new features that will help you unlock the full potential of OpenCV 3 Written by a team of 7 experts, each chapter explores a new aspect of OpenCV to help you make amazing computer-vision aware applications Each chapter is a tutorial for an entire project from start to finish, showing you how to apply OpenCV to solve complete problems Book Description As we become more capable of handling data in every kind, we are becoming more reliant on visual input and what we can do with those self-driving cars, face recognition, and even augmented reality applications and games. This is all powered by Computer Vision. This book will put you straight to work in creating powerful and unique computer vision applications. Each chapter is structured around a central project and deep dives into an important aspect of OpenCV such as facial recognition, image target tracking, making augmented reality applications, the 3D visualization framework, and machine learning. You’ll learn how to make AI that can remember and use neural networks to help your applications learn. By the end of the book, you will have created various working prototypes with the projects in the book and will be well versed with the new features of OpenCV3. What you will learn Execute basic image processing operations and cartoonify an image Build an OpenCV project natively with Raspberry Pi and cross-compile it for Raspberry Pi.text Extend the natural feature tracking algorithm to support the tracking of multiple image targets on a video Use OpenCV 3’s new 3D visualization framework to illustrate the 3D scene geometry Create an application for Automatic Number Plate Recognition (ANPR) using a support vector machine and Artificial Neural Networks Train and predict pattern-recognition algorithms to decide whether an image is a number plate Use POSIT for the six degrees of freedom head pose Train a face recognition database using deep learning and recognize faces from that database

Mastering OpenCV 3, Second Edition, Get hands-on with practical Computer Vision using OpenCV 3. Second edition: April 2017

Understanding Digital Signal Processing, Second Edition（英文版） 对于想学习DSP的朋友来说，非常推荐这本书。内容讲解生动、浅显易懂！

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Over 60 hands-on recipes to help you master the power of Delphi for cross-platform and mobile development on multiple platforms. 本书包含完整的书签，方便阅读。