Stochastic Geometry and Wireless Networks Iⅈ 第一卷以及第二卷

This book was written using a tutorial approach and is intended to appeal to a broad audience. The book covers the fundamentals of short-range wireless networking using ZigBee™ and IEEE 802.15.4™ standards. The ZigBee and IEEE 802.15.4 standards are covered with the same level of detail. In addition to technical details, the book contains high-level overviews that would be informative for a reader who is only interested in understanding the general concept of ZigBee wireless networking. This book provides the big picture of ZigBee wireless networking, from the radio frequency (RF) and physical layer considerations up to the application layer details. Considering the multidisciplinary nature of this book, the required background materials are also provided.

Multiobjective Deep Belief Networks Ensemble for Remaining Useful Life Estimation in Prognostics .pdf

本书是Grégoire Montavon 2012年推出的第二版书，主要介绍神经网络的训练改进技巧、以及表示等等，本书高清无码扫描，附带完整标签，文字可编辑复制，并以保存为长期归档格式PDF/A！堪称完美！强烈推荐！

Recurrent Neural Networks for Prediction offers a new insight into the learning algorithms, architectures and stability of recurrent neural networks and, consequently, will have instant appeal. It provides an extensive background for researchers, academics and postgraduates enabling them to apply such networks in new applications.

computer networks 5th, Andrew Tanenbaum, David Wetherall, Prentice Hall, 2011, Solution, 答案解析

MIT教材Data Networks全部的答案，不是一部分，1-6章都有。

可参看博客：https://blog.csdn.net/luolan9611/article/details/88578720 视觉问题回答（VQA）需要联合图像和自然语言问题，其中许多问题不能直接或清楚地从视觉内容中得到，而是需要从结构化人类知识推理并从视觉内容中得到证实。该论文提出了视觉知识记忆网络（VKMN）来解决这个问题，它将结构化的人类知识和深层视觉特征无缝融入端到端学习框架中的记忆网络中。与现有的利用外部知识支持VQA的方法相比，本文更多地强调了两种缺失的机制。首先是将视觉内容与知识事实相结合的机制。 VKMN通过将知识三元组（主体，关系，目标）和深层视觉特征联合嵌入到视觉知识特征中来处理这个问题。其次是处理从问题和答案对中扩展出多个知识事实的机制。VKMN使用键值对结构在记忆网络中存储联合嵌入，以便易于处理多个事实。实验表明，该方法在VQA v1.0和v2.0基准测试中取得了可喜的成果，同时在知识推理相关问题上优于最先进的方法。

最经典的计算机网络著作。Andrew S. Tanenbaum的成名之作

Long Short Term Memory Networks for Anomaly Detection in Time Series - LSTM在时序数据中的应用