这是我上次发的续集，很详细，很值得看一看

增强学习 经典算法 A3C 论文摘要： We propose a conceptually simple and lightweight framework for deep reinforcement learning that uses asynchronous gradient descent for optimization of deep neural network controllers. We present asynchronous variants of four standard reinforcement learning algorithms and show that parallel actor-learners have a stabilizing effect on training allowing all four methods to successfully train neural network controllers. The best performing method, an asynchronous variant of actor-critic, surpasses the current state-of-the-art on the Atari domain while training for half the time on a single multi-core CPU instead of a GPU. Furthermore, we show that asynchronous actor-critic succeeds on a wide variety of continuous motor control problems as well as on a new task of navigating random 3D mazes using a visual input.

基于AJAX技术Web模型是目前较为热门的网站构架，它不但能使网上用户得到更好得体验，而且能够减轻服务器和带宽的负担。本文将着重介绍AJAX的概念、工作原理以及一个简单的程序示例并同传统的Web应用模型进行了比较

[EBOOK]Asynchronous Circuit Design--Chris.J.Myers(包含源代码) With asynchronous circuit design becoming a powerful tool in the development of new digital systems, circuit designers are expected to have asynchronous design skills and be able to leverage them to reduce power consumption and increase system speed. This book walks readers through all of the different methodologies of asynchronous circuit design, emphasizing practical techniques and real-world applications instead of theoretical simulation. The only guide of its kind, it also features an ftp site complete with support materials. Market: Electrical Engineers, Computer Scientists, Device Designers, and Developers in industry Designers , different , Practical , Techniques , 源代码

介绍 该项目的灵感来自： 我将YOLO v3换成了YOLO v4，并添加了用于异步处理的选项，这大大提高了FPS。 但是，使用异步处理时FPS监视将被禁用，因为它不准确。 另外，我从提取了算法，并将其实现到deep_sort/track.py 。 用于确认轨迹的原始方法仅基于检测到对象的次数，而不考虑检测置信度，从而在发生不可靠的检测时（即低置信度真阳性或高置信度假阳性）导致高跟踪误报率。 轨道过滤算法通过在确认轨道之前计算一组检测次数的平均检测置信度，从而大大降低了这一点。 请参阅下面的比较视频。 低置信度轨道过滤 导航到适当的文件夹以使用低置信度轨道过滤。 上面的视频演示了差异。

LabVIEW

AMC参考库帮助文档说明中文版

#6.3_A3C_(Asynchronous_Advantage_Actor-Critic)_(强化学习_Reinforceme

讲述异步FIFO设计的景点例子，包含verilog源码，仿真，框图等，IC数字设计的基础之一

采用的是matlab官方给的例程学习，ccs程序是通过matlab中的simulink模型直接导出生成的。记得配合博文使用啊！