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Preface xv Introduction xvii Mathematical Notation xix Pseudo-Code xxi Contributors xxvi 1 2D GEOMETRY Useful 2D Geometry 3 Trigonometry Summary 12 Useful Trigonometry 13 Trigonometric Functions at Select Points 18 Triangles 20 Generating Random Poi
This paper proposes a novel scheme for video content-based copy identification dedicated to TV broadcast with a reference video database exceeding 1000 hours of video. It enables the monitoring of a TV channel in soft real-time with a good tolerance
This book isn't an introduction to object-oriented technology or design. Many books already do a good job of that. This book assumes you are reasonably proficient in at least one object-oriented programming language, and you should have some experie
三菱 FX2N 硬件手册 Foreword • This manual contains text, diagrams and explanations which will guide the reader in the correct installation and operation of the FX2N-32DP-IF Profibus-DP Interface Unit. It should be read and understood before attempting to
Using DIB Sections in VB An Easy to Use Class for manipulating DIBSections plus a blindingly quick technique for updating the bits Updated! 17 February 1999 The previous version of this code crashed when run under NT4.0. This was because the cod
What is a DIB Section?A DIB (Device Independent Bitmap) Section is a GDI object like a standard DIB but which additionally provides a pointer to the memory used to store the bitmap bits to which the creating application has direct access. This allow
这本书在国内已经绝版。目录如下 Introduction Dorit S. Hochbaum 0.1 What can approximation algorithms do for you: an illustrative example 0.2 Fundamentals and concepts 0.3 Objectives and organization of this book 0.4 Acknowledgments I Approximation Algorithms for Sc
硕士学位论文 Localization in wireless sensor networks is the process of determining the geographical positions of sensors. Only some of the sensors (anchors) in the networks have prior knowledge about their geographical positions. Localization algorithms
k-means clustering,聚类,用于机器学习和模式识别。 下面是英文介绍：In statistics and machine learning, k-means clustering is a method of cluster analysis which aims to partition n observations into k clusters in which each observation belongs to the cluster with the neares
Pattern selection methods have been traditionally developed with a dependency on a specific classifier. In contrast, this paper presents a method that selects critical patterns deemed to carry essential information applicable to train those types of
绝对棒的开发参考书，开拓思路。 This book isn't an introduction to object-oriented technology or design. Many books already do a good job of that. This book assumes you are reasonably proficient in at least one object-oriented programming language, and you should h
