Real-Time Design Patterns - Robust Scalable Architecture for Real-Time

讲各种实时阴影技术的好书 看目录： 1Introduction 1 1.1Denition...............................3 1.2ImportanceofShadows.......................12 1.3Di›cultyofComputingShadows.................15 1.4Overview...............................19 1.5GeneralInformationfortheReader................20 2BasicShadowTechniques 21 2.1ProjectionShadows.........................22 2.2ShadowMapping..........................31 2.3ShadowVolumes...........................44 2.4StencilShadowVolumes......................48 2.5Transparency.............................72 2.6Summary...............................73 3Shadow-MapAliasing 75 3.1ShadowMappingasSignalReconstruction...........75 3.2InitialSamplingError—Undersampling.............81 3.3ResamplingError..........................87 4Shadow-MapSampling 89 4.1Fitting.................................89 4.2Warping................................93 4.3GlobalPartitioning.........................110 4.4AdaptivePartitioning........................123 4.5View-SampleMapping.......................131 4.6Shadow-MapReconstruction...................134 4.7TemporalReprojection.......................136 4.8Cookbook...............................137 5FilteredHardShadows 139 5.1FiltersandShadowMaps......................140 5.2ApplicationsofFiltering......................144 5.3PrecomputingLargerFilterKernels................147 5.4Summary...............................160 6Image-BasedSoft-ShadowMethods 161 6.1Introduction.............................161 6.2Basics.................................166 6.3AReferenceSolution........................172 6.4AugmentingHardShadowswithPenumbrae..........174 6.5BlurringHard-Shadow-TestResults................178 6.6FilteringPlanarOccluderImages.................187 6.7ReconstructingandBack-ProjectingOccluders.........191 6.8UsingMultipleDepthMaps....................204 6.9Summary...............................206 7Geometry-BasedSoft-ShadowMethods 209 7.1PlausibleShadowsbyGeneratingOuterPenumbra.......209 7.2InnerandOuterPenumbra..........

Time Series Analysis With Applications in R (Springer)

这是一本由Sen M. Kuo, Bob H. Lee, Wenshun Tian等编写的实时数字信号处理，其中包括了信号处理的基本概念外，还有应用，例如有以下几章：8 - Digital Signal Generators，9 - Dual-Tone Multi-Frequency Detection，10 - Adaptive Echo Cancellation，11 - Speech Coding Techniques，12 - Speech Enhancement Techniques，13 - Audio Signal Processing，14 - Channel Coding Techniques等。

高清PDF电子书， 关于卡尔曼滤波和小波的，经典书籍，第四版了 Kalman filtering is an optimal state estimation process applied to a dynamic system that involves random perturbations. More precisely, the Kalman filter gives a linear, unbiased, and minimum error variance recursive algorithm to optimally estimate the unknown state of a dynamic system from noisy data taken at discrete real-time. It has been widely used in many areas of industrial and government applications such as video and laser tracking systems, satellite navigation, ballistic missile trajectory estimation, radar, and fire control. With the recent development of high-speed computers, the Kalman filter has become more useful even for very complicated real-time applications. In spite of its importance, the mathematical theory of Kalman filtering and its implications are not well understood even among many applied mathematicians and engineers. In fact, most practitioners are just told what the filtering algorithms are without knowing why they work so well. One of the main objectives of this text is to disclose this mystery by presenting a fairly thorough discussion of its mathe- matical theory and applications to various elementary real-time problems

Aimed at econometricians who have completed at least one course in time series modeling, Multiple Time Series Modeling Using the SAS VARMAX Procedure will teach you the time series analytical possibilities that SAS offers today. Estimations of model parameters are now performed in a split second. For this reason, working through the identifications phase to find the correct model is unnecessary. Instead, several competing models can be estimated, and their fit can be compared instantaneously. Consequently, for time series analysis, most of the Box and Jenkins analysis process for univariate series is now obsolete. The former days of looking at cross-correlations and pre-whitening are over, because distributed lag models are easily fitted by an automatic lag identification method. The same goes for bivariate and even multivariate models, for which PROC VARMAX models are automatically fitted. For these models, other interesting variations arise: Subjects like Granger causality testing, feedback, equilibrium, cointegration, and error correction are easily addressed by PROC VARMAX. One problem with multivariate modeling is that it includes many parameters, making parameterizations unstable. This instability can be compensated for by application of Bayesian methods, which are also incorporated in PROC VARMAX. Volatility modeling has now become a standard part of time series modeling, because of the popularity of GARCH models. Both univariate and multivariate GARCH models are supported by PROC VARMAX. This feature is especially interesting for financial analytics in which risk is a focus. This book teaches with examples. Readers who are analyzing a time series for the first time will find PROC VARMAX easy to use; readers who know more advanced theoretical time series models will discover that PROC VARMAX is a useful tool for advanced model building.

KinectFusion: Real-time 3D Reconstruction and Interaction Using a Moving Depth Camera是一片详细介绍kinect sdk中kinectfusion的论文，kinectfusion能够使用kinect进行实时地三维重建。这篇论文是每个使用kinect进行三维重建的工作者都应该看的文章，所以我将它进行了翻译。由于本人水平有限，部分较为复杂的算法没有进行翻译，其他均有翻译。翻译全文共6900余字，仅供大家参考。

Real-time Rendering 第三版，非常好的实时渲染的书，非扫描版。而且是彩色版

这是笔者2019.9下载的UCR数据集，其中有较多的时间序列数据，方便大家下载学习，特此分享给大家。(在介绍中,没有说不许传播,如有侵权,会立即删除.)

失效时间的统计分析，这是一本经典教材， 关于作者 JOHN D. KALBFLEISCH，博士，密歇根大学安娜堡分校和加拿大安大略省滑铁卢大学生物统计学教授。 ROSS L. PRENTICE，博士，弗雷德哈钦森癌症研究中心和西雅图华盛顿大学的生物统计学教授