5G信号处理

5G wireless technology is developing at an explosive rate and is one of the biggest areas of research within academia and industry. In this rapid development, signal processing techniques are playing the most important role. In 2G, 3G and 4G, the peak service rate was the dominant metric for performance. Each of these previous generations was defned by a standout signal processing technology that represented the most important advance made. In 2G, this technology was time-division multiple access (TDMA); in 3G, it was code-division multiple access (CDMA); and in 4G, it was orthogonal frequency-division multiple access (OFDMA). However, this will not be the case for 5G systems – there will be no dominant performance metric that defnes requirements for 5G technologies. Instead, a number of new signal processing techniques will be used to continuously increase peak service rates, and there will be a new emphasis on greatly increasing capacity, coverage, effciency (power, spectrum, and other resources), flexibility, compatibility, reliability and convergence. In this way, 5G systems will be able to handle the explosion in demand arising from emerging applications such as big data, cloud services, and machine-to-machine communication.

Intel Threading Building Blocks

Multi-core systems have arrived. Parallel programming models are needed to enable the creation of programs that exploit them. A good deal of education is needed to help sequential programmers adapt to the requirements of this new technology. This book represents progress on both of these fronts.

The CUDA Handbook

The CUDA Handbook begins where CUDA by Example (Addison-Wesley, 2011) leaves off, discussing CUDA hardware and software in greater detail and covering both CUDA 5.0 and Kepler. Every CUDA developer, from the casual to the most sophisticated, will find something here of interest and immediate usefulness. Newer CUDA developers will see how the hardware processes commands and how the driver checks progress; more experienced CUDA developers will appreciate the expert coverage of topics such as the driver API and context migration, as well as the guidance on how best to structure CPU/GPU data interchange and synchronization.

深度学习与NLP

Recent advancements in AI resulted in increased availability of conversational assistants that can help with tasks such as seeking times to schedule an event and creating a calendar entry at that time, finding a restaurant and booking a table there at a certain time. However, creating automated agents with human-level intelligence still remains one of the most challenging problems of AI. One key component of such systems is conversational language understanding, which is a holy grail area of research for decades, as it is not a clearly defined task but relies heavily on the AI application it is used for. Nevertheless, this chapter attempts to compile the recent deep learning based literature on such goal-oriented conversational language understanding studies, starting with a historical perspective, pre-deep learning era work, moving toward most recent advances in this field

Mastering Machine Learning With scikit-learn

This book examines machine learning models including logistic regression, decision trees, and support vector machines, and applies them to common problems such as categorizing documents and classifying images. It begins with the fundamentals of machine learning, introducing you to the supervised-unsupervised spectrum, the uses of training and test data, and evaluating models. You will learn how to use generalized linear models in regression problems, as well as solve problems with text and categorical features. You will be acquainted with the use of logistic regression, regularization, and the various loss functions that are used by generalized linear models. The book will also walk you through an example project that prompts you to label the most uncertain training examples. You will also use an unsupervised Hidden Markov Model to predict stock prices.

2.4GHz接收机射频前端设计

．4GHz ISM频段的接收机的设计和研究在无线通信领域具有十 分重要的意义．本文详细深入的讨论了无线接收机的结构体系和射频接收前端中关键模 块的原理、设计、测试工作

sklearn开发指导书

sklearn中包含了大量的优质的数据集，在你学习机器学习的过程中，你可以通过使用这些数据集实现出不同的模型，从而提高你的动手实践能力，同时这个过程也可以加深你对理论知识的理解和把握。

基于AD9361的软件无线电硬件平台设计与实现

本论文主要研究了基于 AD9361 软件无线电硬件平台的设计与实现。论文首 先介绍了软件无线电的研究背景和意义， 其发展的现状和前景，软件无线电的定 义原理以及软件无线电的关键技术。然后制定了软件无线电硬件平台的总体方案 设计，并着重介绍了该硬件平台的各个模块硬件电路的实现方案。最后对硬件平 台各个模块进行了单独测试以及整个系统的综合测试及系统测试。

基于 ZYNQ 7020 的 FPGA + ARM 开发

ZynqTM-7000 系列芯片是基于 Xilinx 的可扩展处理器平台架构(Extensible Processing Platform, EPP), 将双核 ARM CortexTM-A9 处理器和 FPGA 可编程逻辑单元集成在一颗单芯片中,从而构成所谓的 PS(Processing System)加 PL(Programmable Logic)的单芯片 SoC 解决方案。

802.11n 基于gnuradio实现

802.11n 基于gnuradio实现 开源软件无线电（Gnuradio）或 开源软件定义无线电，是一个对学习、构建和部署软件定义无线电系统的免费软件工具包。发起于2001年，Gnuradio 现在成为GNU 的正式项目之一。慈善家John Gilmore 发起并捐助$320,000.00 (US) 给Eric Blossom 用来构建代码和维护。