自动化回归测试在Java项目中的实现.文中首先介绍了软件 自动化测试和回归测试的概念，然后以一个用 Java语言开发的项目CADS为例，详细阐述了如何在 Jav...

Spring Framework 开发参考手册-Spring Framework to develop a reference manual

The Kalman filter is a mathematical power tool that is playing an increasingly important role in computer graphics as we include sensing of the real world in our systems. The good news is you don’t have to be a mathematical genius to understand and effectively use Kalman filters. This tutorial is designed to provide developers of graphical systems with a basic understanding of this important mathematical tool.

sun公司的docs只有英文与日文的，这是中文版本的API-the docs only in English and Japanese, which is the Chinese version of the API

IBM汇编语言程序设计（温，沈 清华版）课后习题答案，TXT文档-IBM Assembly Language Programming (temperature, Shen Tsinghua version) after exercise answer, TXT files

county, random population coordinates were generated using the complete spatial randomness (CSR) function in S-PLUS. Then, the background information was attached to each individual county based on the county?s distribution for the class of interest. Finally, all counties were merged into a single dataset that describes the whole state-county. random population coordinates were generated using the complete spatial randomness (CSR) fu nction in S-PLUS. Then, the background information was attached to eac h individual county based on the county"s distri bution for the class of interest. Finally, all counties were merged into a single dataset t hat describes the whole state

C语言编程宝典，绝对经典的书籍，值得下载！-C language programming canon that is absolutely classic books, it is worth to download!

Pricinples and fundamentals of electrical engineering-Pricinples and fundamentals of electrica l engineering

Cisco advanced routeing ebootk, this is pdf file and you had to use the Adobe 8 to see it. the part1

The celebrated Kalman filter, rooted in the state-space formulation or linear dynamical systems, provides a recursive solution to the linear optimal filtering problem. It applies to stationary as well as nonstationary environments. The solution is recursive in that each updated estimate of the state is computed from the previous estimate and the new input data, so only the previous estimate requires storage. In addition to eliminating the need for storing the entire 1 past observed data, the Kalman filter is computationally more efficient than computing the estimate directly from the entire past observed data at each step of the filtering process.

该书详细的介绍了ＬＩＮＵＸ运行机理，是该领域很权威的一本书-book detailed introduction to the Linux operating mechanism is that the field is an authoritative book