DFT工具 DFT工具是一个帮助python软件包，用于解析，操作和显示与密度泛函理论（DFT）代码有关的文本数据。 更多信息和文档： :

“ RMAT”包 （注意：此程序包很容易开发。语法在不断优化，并且经常重命名。） 开发RMAT软件包是为了模拟各种类型的常见随机矩阵及其合奏。 其主要功能包括： 模拟各种随机矩阵 模拟这些随机矩阵的合奏 可视化这些矩阵集合的特征值谱 包括的矩阵是： 普通矩阵 b = 1,2,4的Beta合奏 b> 0的广义Beta集合 随机矩阵 参数稀疏性的随机矩阵 三对角矩阵 带矩阵 对于某些矩阵，相关函数中包含自由参数： 实值/复值条目 对称/ Hermitian矩阵

Two Dimensional Phase Unwrapping: Theory, Algorithms and Software by Dennis C. Ghiglia & Mark D. Pritt Part 2 of 4

介绍最新的启发式搜索算法，从数据的表示，到算法的介绍，算法的实现，以及算法的应用，非常详细，文献非常新，是作为深入研究搜索算法的一本不可多得的好书。有了好东西就要跟大家分享~~~

这是一本关于随机建模和模糊建模的好书，非常经典！

Title: Speech Enhancement: Theory and Practice, 2nd Edition Author: Philipos C. Loizou Length: 711 pages Edition: 2 Language: English Publisher: CRC Press Publication Date: 2013-02-25 ISBN-10: 1466504218 ISBN-13: 9781466504219 With the proliferation of mobile devices and hearing devices, including hearing aids and cochlear implants, there is a growing and pressing need to design algorithms that can improve speech intelligibility without sacrificing quality. Responding to this need, Speech Enhancement: Theory and Practice, Second Edition introduces readers to the basic problems of speech enhancement and the various algorithms proposed to solve these problems. Updated and expanded, this second edition of the bestselling textbook broadens its scope to include evaluation measures and enhancement algorithms aimed at improving speech intelligibility. Fundamentals, Algorithms, Evaluation, and Future Steps Organized into four parts, the book begins with a review of the fundamentals needed to understand and design better speech enhancement algorithms. The second part describes all the major enhancement algorithms and, because these require an estimate of the noise spectrum, also covers noise estimation algorithms. The third part of the book looks at the measures used to assess the performance, in terms of speech quality and intelligibility, of speech enhancement methods. It also evaluates and compares several of the algorithms. The fourth part presents binary mask algorithms for improving speech intelligibility under ideal conditions. In addition, it suggests steps that can be taken to realize the full potential of these algorithms under realistic conditions. What’s New in This Edition Updates in every chapter A new chapter on objective speech intelligibility measures A new chapter on algorithms for improving speech intelligibility Real-world noise recordings (on accompanying CD) MATLAB® code for the implementation of intelligibility measures (on accompanying CD) MATLAB and C/C++ code for the implementation of algorithms to improve speech intelligibility (on accompanying CD) Valuable Insights from a Pioneer in Speech Enhancement Clear and concise, this book explores how human listeners compensate for acoustic noise in noisy environments. Written by a pioneer in speech enhancement and noise reduction in cochlear implants, it is an essential resource for anyone who wants to implement or incorporate the latest speech enhancement algorithms to improve the quality and intelligibility of speech degraded by noise. Includes a CD with Code and Recordings The accompanying CD provides MATLAB implementations of representative speech enhancement algorithms as well as speech and noise databases for the evaluation of enhancement algorithms. Table of Contents Chapter 1 Introduction Chapter 2 Discrete-Time Signal Processing and Short-Time Fourier Analysis Chapter 3 Speech Production and Perception Chapter 4 Noise Compensation by Human Listeners Chapter 5 Spectral-Subtractive Algorithms Chapter 6 Wiener Filtering Chapter 7 Statistical-Model-Based Methods Chapter 8 Subspace Algorithms Chapter 9 Noise-Estimation Algorithms Chapter 10 Evaluating Performance of Speech Enhancement Algorithms Chapter 11 Objective Quality and Intelligibility Measures Chapter 12 Comparison of Speech Enhancement Algorithms Chapter 13 Algorithms That Can Improve Speech Intelligibility Appendix A: Special Functions and Integrals Appendix B: Derivation of the MMSE Estimator Appendix C: MATLAB ® Code and Speech/Noise Databases

What is information? How do we quantify or measure the amount of information that is present in a file of data, or a string of text? How do we encode the information so that it can be stored efficiently, or transmitted reliably?

Weak Consistency - A Generalized Theory and Optimistic Implementations for Distributed Transactions.pdf Current commercial databases allow application programmers to trade off consistency for performance. However, existing definitions of weak consistency levels are either imprecise or they disallow efficient implementation techniques such as optimism. Ruling out these techniques is especially unfortunate because commercial databases support optimistic mechanisms. Furthermore, optimism is ...

Distributed consensus is fundamental to building fault-tolerant systems. It allows a collection of machines to work as a coherent group that can survive the failures of some of its members. Unfortunately, the most common consensus algorithm, Paxos, is widely regarded as difficult to understand and implement correctly. This dissertation presents a new consensus algorithm called Raft, which was designed for understandability.

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