Power Spectral Density using PWELCH vs PSD created by FFT.zip，这是

Book Description: Solve your C programming problems with practical and informative recipes. This book covers various aspects of C programming including the fundamentals of C, operators and expressions, control statements, recursion, and user-defined functions. Each chapter contains a series of recipes that you can easily reference to quickly find the answers you are looking for. C Recipes also contains recipes and solutions for problems in memory management, arrays, standard input and output, structures and unions, pointers, self-referential structures, data files, pre-processor directives, and library functions. What You Will Learn Master operators and expressions Write user-defined functions Work with structures and unions Use pointers Define self referential structures Leverage library functions Who This Book Is For Those with some experience in C programming.

During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It is a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for 'wide' data (p bigger than n), including multiple testing and false discovery rates.

Cubase LE AI Elements 8.exe

MATLAB光谱图绘制，能够画出可见光波长下的光谱图

Finite-element Methods for Electromagnetics英文清晰PDF

高级计算机体系结构 用书（第五版）

这是关于非线性有限元方法的电子书，高清，最新版本，经典著作，英文版

MARTIN HAENGGI is a Professor of Electrical Engineering, and a Concurrent Professor of Applied and Computational Mathematics and Statistics, at the University of Notre Dame, Indiana.

有限元分析教程