LCM1602A

说明：  图书使用Excel和VBA的高级财务建模英文版(Advanced Modeling in Finance Using Excel and VBA)

本书是经典畅销图书《Python 核心编程（第二版）》的全新升级版本，总共分为 3 部分。 第 1 部分讲解了 Python 的一些通用应用，包括正则表达式、网络编程、Internet 客户端编程、多线程编程、GUI 编程、数据库编程、Microsoft Office 编程、扩展 Python 等内容。 第 2 部分 讲解了与 Web 开发相关的主题，包括 Web 客户端和服务器、CGI 和 WSGI 相关的 Web 编程、Diango Web 框架、云计算、高级 Web 服务。第 3 部分则为一个补充/实验章节，包括文本处理以及一些其他内容。 本书适合具有一定经验的 Python 开发人员阅读(This book is a new upgraded version of the classic best-selling book Python Core Programming (2nd Edition). It is divided into three parts. Part 1 explains some general applications of Python, including regular expressions, network programming, Internet client programming, multi-threading programming, GUI programming, database programming, Microsoft Office programming, extension of Python and so on. Part 2 Topics related to Web development are explained, including Web client and server, CGI and WSGI related Web programming, Diango Web framework, cloud computing, advanced Web services. Part 3 is a supplementary/experimental chapter, including text processing and some other contents. This book is suitable for Python developers with some experience.)

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Reference book for sensor networks.

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神经网络是一种模拟人脑的神经网络，以期能够实现类人工智能的机器学习 技术。 本书揭示神经网络背后的概念，并介绍如何通过Python实现神经网络。全书 分为3章和两个附录。第1章介绍了神经网络中所用到的数学思想。第2章介绍使 用Python实现神经网络，识别手写数字，并测试神经网络的性能。第3章带领读 者进一步了解简单的神经网络，观察已受训练的神经网络内部，尝试进一步改善 神经网络的性能，并加深对相关知识的理解。附录分别介绍了所需的微积分知识 和树莓派知识。 本书适合想要从事神经网络研究和探索的读者学习参考，也适合对人工智 能、机器学习和深度学习等相关领域感兴趣的读者阅读。(Python Neural Network Programming)

说明：  想学习黑客技术，进行逆向编程，同时提高编程技术的可以下载学习(Want to learn hacker technology, reverse programming, while improving the programming technology can be downloaded to learn)

本书运用现代信号处理的理论，系统地介绍了分数阶Fourier变换的定义与特性，分数阶Fourier分析的基本原理与方法及其典型的应用。内容包括：分数阶Fourier变换的起源与发展、定义与基本特性；分数阶Fourier变换与其他时频分析工具的关系；分数阶Fourier变换的快速算法；分数阶Fourier变换在信号的检测与参数估计、雷达信号处理、时频域滤波以及通信信号处理中的应用。(The book is the use of modern signal processing theory, the system introduces the definition and characteristics of the fractional Fourier transform, fractional Fourier analysis of the basic principles and methods of its typical applications. Include: the origin and development of the fractional Fourier transform, the definition and basic characteristics fractional Fourier transform relationship with other time-frequency analysis tool fractional Fourier transform algorithm fractional Fourier transform in signal detection and parameter estimation The radar signal processing, time and frequency domain filtering and communication signal processing applications.)

Interference Analysis and Reduction for Wireless Systems.pdf

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