4G LTELTE-Advanced for Mobile Broadband (Second Edition) Base on Release 11 Second edition 2014 Erik Dahlman Stefan Parkvall Johan Sko¨ld

Linux Driver Development for Embedded Processors – Second Edition 版本: Learn to develop Linux embedded drivers with kernel 4.9 LTS The flexibility of Linux embedded, the availability of powerful, energy efficient processors designed for embedded computing and the low cost of new processors are encouraging many industrial companies to come up with new developments based on embedded processors. Current engineers have in their hands powerful tools for developing applications previously unimagined, but they need to understand the countless features that Linux offers today. This book will teach you how to develop device drivers for Device Tree Linux embedded systems. You will learn how to write different types of Linux drivers, as well as the appropriate APIs (Application Program Interfaces) and methods to interface with kernel and user spaces. This is a book is meant to be practical, but also provides an important theoretical base. More than twenty drivers are written and ported to three different processors. You can choose between NXP i.MX7D, Microchip SAMA5D2 and Broadcom BCM2837 processors to develop and test the drivers, whose implementation is described in detail in the practical lab sections of the book. Before you start reading, I encourage you to acquire any of these processor boards whenever you have access to some GPIOs, and at least one SPI and I2C controllers. One of the boards used to implement the drivers is the famous Raspberry PI 3 Model B board. You will learn how to develop drivers, from the simplest ones that do not interact with any external hardware, to drivers that manage different kind of devices: accelerometers, DACs, ADCs, RGB LEDs, Multi-Display LED controllers, I/O expanders, and Buttons. You will also develop DMA drivers, drivers that manage interrupts, and drivers that write/read on the internal registers of the processor to control external devices. To easy the development of some of these drivers, you will use different types of Frameworks:

How to Design Programs, Second Edition

Learning OpenCV 3 Computer Vision with Python英文第二版, 高清, 接下来共享随书代码

kkphoon文章给出了基于K-L展开的非高斯非平稳随机过程模拟（kkphoon的该篇文章在matlab中的实现可在我另一份上传资源里找到，对于协方差函数的特征函数与特征值的数值解，另一份资源中也将给出）

信号配时手册第二版，介绍了与信号配时相关的基础的和先进理念。

The Visual Display of Quantitative Information(Second Edition)

Mastering TypeScript - Second Edition by Nathan Rozentals English | 6 Mar. 2017 | ISBN: 1786468719 | 651 Pages | EPUB/PDF (conv) | 12.4 MB Key Features Start with the basics, then enhance your knowledge with in-depth discussions on language features, third-party libraries, design patterns and more Practical examples that show how to use TypeScript with popular frameworks, including Backbone, Angular 2, React, Aurelia, Node and others Focus on test-driven development to build high quality applications that are modular, scalable and adaptable Book Description The TypeScript language, compiler and open-source development toolset brings JavaScript development up to the enterprise level. It allows us to use ES5, ES6 and ES7 JavaScript language features today - including classes, interfaces, generics, modules and more. It's simple typing syntax enables building large, robust applications using object-oriented techniques and industry standard design principles. Packed with practical, real-world examples, this book is a guide to bringing the benefits of strongly typed, object-oriented programming and design principles into the JavaScript development space. Starting with core language features, and working through more advanced topics such as generics and asynchronous programming techniques, you will learn how to gain maximum benefit from your JavaScript development with TypeScript. With a strong focus on test-driven development, and coverage of many popular and in-demand JavaScript frameworks, you can fast-track your TypeScript knowledge to a professional level. By the end of this book, you will be able to confidently build TypeScript applications, whether you are targeting Angular 2, Aurelia, React, Backbone, Node or any other JavaScript framework. What you will learn Gain an insight into core and advanced TypeScript language features including inheritance, generics, asynchronous programming techniques, promises, decorators and more Integrate your existing JavaScrip

QGIS Python Programming Cookbook - Second Edition by Joel Lawhead English | 14 Mar. 2017 | ASIN: B01MRP7T3B | 464 Pages | AZW3 | 9.26 MB Master over 170 recipes that will help you turn QGIS from a desktop GIS tool into a powerful automated geospatial framework About This Book Delve into the undocumented features of the QGIS API Get a set of user-friendly recipes that can automate entire geospatial workflows by connecting Python GIS building blocks into comprehensive processes This book has a complete code upgrade to QGIS 2.18 and 30 new, valuable recipes Who This Book Is For This book is for geospatial analysts who want to learn more about automating everyday GIS tasks as well as programmers responsible for building GIS applications. The short, reusable recipes make concepts easy to understand and combine so you can build larger applications that are easy to maintain. What You Will Learn Use Python and QGIS to produce captivating GIS visualizations and build complex map layouts Find out how to effectively use the poorly-documented and undocumented features of the QGIS Python API Automate entire geospatial workflows by connecting Python GIS building blocks into comprehensive processes Create, import, and edit geospatial data on disk or in-memory Change QGIS settings programmatically to control default behavior Automatically generate PDF map books Build dynamic forms for field input In Detail QGIS is a desktop geographic information system that facilitates data viewing, editing, and analysis. Paired with the most efficient scripting language—Python, we can write effective scripts that extend the core functionality of QGIS. Based on version QGIS 2.18, this book will teach you how to write Python code that works with spatial data to automate geoprocessing tasks in QGIS. It will cover topics such as querying and editing vector data and using raster data. You will also learn to create, edit, and optimize a vector layer for faster queries, reproject a vector layer, reduce the number of vertices in a vector layer without losing critical data, and convert a raster to a vector. Following this, you will work through recipes that will help you compose static maps, create heavily customized maps, and add specialized labels and annotations. As well as this, we'll also share a few tips and tricks based on different aspects of QGIS. Style and approach This book follows a recipe-based problem-solution approach to address and dispel challenges faced when implementing and using QGIS on a regular basis.

earning Data Mining with Python - Second Edition by Robert Layton English | 4 May 2017 | ASIN: B01MRP7VFV | 358 Pages | AZW3 | 2.85 MB Key Features Use a wide variety of Python libraries for practical data mining purposes. Learn how to find, manipulate, analyze, and visualize data using Python. Step-by-step instructions on data mining techniques with Python that have real-world applications. Book Description This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. This book covers a large number of libraries available in Python, including the Jupyter Notebook, pandas, scikit-learn, and NLTK. You will gain hands on experience with complex data types including text, images, and graphs. You will also discover object detection using Deep Neural Networks, which is one of the big, difficult areas of machine learning right now. With restructured examples and code samples updated for the latest edition of Python, each chapter of this book introduces you to new algorithms and techniques. By the end of the book, you will have great insights into using Python for data mining and understanding of the algorithms as well as implementations. What you will learn Apply data mining concepts to real-world problems Predict the outcome of sports matches based on past results Determine the author of a document based on their writing style Use APIs to download datasets from social media and other online services Find and extract good features from difficult datasets Create models that solve real-world problems Design and develop data mining applications using a variety of datasets Perform object detection in images using Deep Neural Networks Find meaningful insights from your data through intuitive visualizations Compute on big data, including real-time data from the internet About the Author Robert Layton is a data scientist working mainly on text mining problems for industries incl