STAP

一个C和C++的函授参考手册，希望能够成为您编程的好帮手。(A C and C++ Correspondence reference manual, I hope to become a good helper of your programming.)

光學的書,歡迎需要光學相關知識的人來索取.希望對大家有幫助(the book of optics.if you need this. please download.)

本书不仅回顾了通信信号处理的经典研究领域，如自适应均衡、信道建模和识别、多用户检测和阵列处理，而且分析研究了一些新领域，如自适应编码调制、多输入多输出（MIMO）系统、分集合并和时频分析。此外，本书还探讨了神经网络、蒙特卡洛马尔可夫链和混沌等新兴技术，并对未来移动通信具有发展前途的方法进行了很好的概括性阐述。(The book investigates classical SP areas such as adaptive equalization, channel modeling and identification, multi-user detection, and array processing. It also investigates newer areas such as adaptive coded modulation, multiple-input multiple-output (MIMO) systems, diversity combining, and time-frequency analysis. It explores emerging techniques such as neural networks, Monte Carlo Markov Chain (MCMC) methods, and Chaos. It offers an excellent tutorial survey of promising approaches for future mobile communications such as cross-layer design in multi-access networks and adaptive wireless networks.)

英文教材：《深入浅出，使用python编程》(python learning in English)

ansys 导入到adams中做刚柔耦合分析方法二，采用质量单元mass21，希望大家在adams中做刚柔耦合分析有所帮助(ansys and adams work together)

模糊理论和神经网络的基础与应用，该书很有深度，值得仔细阅读。(Fuzzy theory and neural network-based and application, the book is very profound, worthy of careful reading.)

认知无线电是一种用于提高无线电通信频谱利用率的新的智能技术. 首先简述认知无线电的背景和概念,针 对认知无线电的频谱感知功能,详细地分析基于能量检测的频谱检测方法,在此基础上研究了噪声方差的不确定 性对检测性能的影响. 针对无线信号检测具有本地局域性和能量检测存在信噪比极限的特点,提出一种分布式有 限合作检测机制,推导出基于“OR”规则的有限合作机制的检测概率,并进行Monte Carlo仿真.(Cognitive radio is a radio communications spectrum used to improve the efficiency of the new smart technology. First, the background and outlined the concept of cognitive radio, spectrum sensing for cognitive radio capabilities, a detailed analysis of the spectrum based on energy detection test In this study the noise variance based on the uncertainty of the detection performance. for wireless signal detection with local detection of localized and there is signal to noise ratio limit of the energy characteristics of a distributed cooperative detection mechanism, derived out based on " OR" rules of the detection probability of the limited cooperation mechanism and conduct Monte Carlo simulation.)

说明：  关于Python的一些资料，帮助快速学习Python(The Guide of Python Quickly)

反卷积和信号复原是信号处理技术中具有理论挑战性的分支。由于应用广泛，它一直是研究热点。有关的研究报告散布于各种专业学术技术刊物和书籍。但对于准备从事信号处理的各专业学生和研究人员还缺乏一本反映近期发展、具有引导性和系统性的书。本书希望弥补这种不足。作者对本领域所需要的基础进行了系统的整理，力求本书能包括主要基础，反映重要进展、难点和发展方向。书中强调了反卷积问题的物理起源、理论方法的要点、适应范围和限制；包括了若干程序例子和实际数据，可为读者进入应用提供帮助；同时又包括了系统深入的理论基础和前沿发展，可满足希望进入前沿研究读者的需要。(Deconvolution and signal recovery is a signal processing technology, a branch of theoretical challenge. Due to its wide, it has been a research focus. The study report is dispersed in the various professional academic and technical journals and books. But prepared to engage in signal processing for professional students and researchers still lack a reflect recent developments, with leading and systematic book. This book can compensate for this deficiency. The authors in this area needed a basis for a systematic order, and strive to include the main basis of this book, reflecting the significant progress, problems and development direction. The book emphasizes the physical origin of deconvolution problems, the main points of theoretical approaches to meet the scope and restrictions includes a number of procedural examples and actual data, can help the reader into the application the same time, the system includes in-depth theoretical basis and leading-edge the development of cutting-e)

说明：  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)