Although portfolio management didn't change much during the 40 years after the seminal works of Markowitz and Sharpe, the development of risk budgeting techniques marked an important milestone in the deepening of the relationship between risk and asset management. Risk parity then became a popular financial model of investment after the global financial crisis in 2008. Today, pension funds and institutional investors are using this approach in the development of smart indexing and the redefinition of long-term investment policies. Written by a well-known expert of asset management and risk parity, Introduction to Risk Parity and Budgeting provides an up-to-date treatment of this alternative method to Markowitz optimization. It builds financial exposure to equities and commodities, considers credit risk in the management of bond portfolios, and designs long-term investment policy. The first part of the book gives a theoretical account of portfolio optimization and risk parity. The author discusses modern portfolio theory and offers a comprehensive guide to risk budgeting. Each chapter in the second part presents an application of risk parity to a specific asset class. The text covers risk-based equity indexation (also called smart beta) and shows how to use risk budgeting techniques to manage bond portfolios. It also explores alternative investments, such as commodities and hedge funds, and applies risk parity techniques to multi-asset classes. The book's first appendix provides technical materials on optimization problems, copula functions, and dynamic asset allocation. The second appendix contains 30 tutorial exercises. Solutions to the exercises, slides for instructors, and Gauss computer programs to reproduce the book's examples, tables, and figures are available on the author's website.

3D全息图像可以通过再现3D场景的光线来提供真实的3D内容，并且被认为是未来3D电视的有前途的技术。 视差信息是3D全息图像的首要内在特征。 提出了一种基于HEVC的基于视差补偿的3D全息图像编码算法。 为了产生真实的差异，我们 在视差匹配过程中向外扩展可用区域，而不是将当前编码块分为四个部分。 实验结果表明， 与原始HEVC标准相比，该方法与原始HEVC帧内预测和经典TMP算法相比，具有可观的收益，并且复杂度增加。

利用VC结合OPENCV编写的图像匹配生成视差图像的程序。

Kolmogorov and Zabih’s graph cuts stereo matching algorithm by Vladimir Kolmogorov and Pascal Monasse This software is linked to the IPOL article [1], which gives a detailed description of the algorithm.

提出了两种新型的准循环低密度奇偶校验（QC-LDPC）的代数构造 代码。 这两种构造是在乘法和乘法上实现的。 两个指定基本矩阵的加性矩阵分散，其中 是基于乘法的 和循环基团。 另外，代码构造中的制作技术可以 也适用于两种构造。 仿真结果表明 本文生成的代码在迭代中表现良好 在AWGN频道上解码。 该代码具有优于 Maykay代码在代码性能的某些方面。 同时， 本文构建的代码在迭代中收敛非常快 解码，这是高吞吐量的重要属性 通讯系统。

matlab 视差图计算代码光流视差误差计算和可视化 该存储库通过基于真实值评估和可视化流误差和视差误差，为光流算法提供了比较工具。 该代码已在 MATLAB 中实现，它以一种易于使用的方式集成了计算、可视化和编程。 快速开始 为了快速理解基本概念和实现，运行 demo.m，它接受地面实况和估计的流量和视差图作为光流误差和视差误差计算和显示的输入。 光流数据集 请参阅这篇关于“光流算法的评估数据集和基准：综述”的评论论文，以选择优选数据集以用于特定任务和培训的关键实施： 用法 流程演示 flow_read() → 从 PNG 图像加载流场 F flow_visualization → 以 u 和 v 作为函数的输入显示光流的颜色图和可视化（这里 u 和 v 分别指流场的水平和垂直分量）并输出循环编码的 uint8 图像flow_error → 计算流场和地面实况之间的流量误差flow_error_image → 显示流场和地面实况之间的流动误差flow_write → 将流场 F 保存为 png 格式 立体声演示 disp_read() → 从 PNG 图像加载视差图 D stereo

一种低复杂度和低存储需求的turbo架构LDPC码，熊磊，，本文提出了一种具有低复杂度和低存储需求的并行级联码—并行交织级联Gallager码（PICGC）。PICGC兼具了长LDPC码优秀性能和短LDPC码的低编�

Disparity estimation for binocular stereo images finds a wide range of applications. Traditional algorithms may fail on featureless regions, which could be handled by high-level clues such as semantic segments. In this paper, we suggest that appropriate incorporation of semantic cues can greatly rectify prediction in commonly-used disparity estimation frameworks. Our method conducts semantic feature embedding and regularizes semantic cues as the loss term to improve learning disparity. Our unified model SegStereo employs semantic features from segmentation and introduces semantic softmax loss, which helps improve the prediction accuracy of disparity maps. The semantic cues work well in both unsupervised and supervised manners. SegStereo achieves stateof-the-art results on KITTI Stereo benchmark and produces decent prediction on both CityScapes and FlyingThings3D datasets.

作者：Sarah J. Johnson（其它的无需详细描述，仅作者的大名只要是搞LDPC研究的人，无人不知） By: Sarah J. Johnson Publisher: Cambridge University Press Pub. Date: November 19, 2009 Print ISBN-13: 978-0-521-87148-8

这一个基于双目视差测距的PPT，很适合实验室、研究所等各个场合的汇报。PPT中包含了测距的背景、测距原理、整体的思路、所用方法(BM)、以及最终的结果的展示。希望可以帮助到大家。因本人学术有限，不免出现一些错误，希望各位大佬多多提出意见。若有人想要关于本PPT的代码，可以评论向我要哦。