该资源给出了论文 Selective Kernel Networks 整体的思维导图情况，可以更方便的加深对论文的理解与应用，所使用的软件是 MindMaster

教材stochastic geometry for wireless networks MARTIN HAENGGI

一本关于无线传感器网络的书，个人认为写得不错！

This book targets engineers and researchers familiar with basic computer architecture concepts who are interested in learning about on-chip networks. This work is designed to be a short synthesis of the most critical concepts in on-chip network design. It is a resource for both understanding on-chip network basics and for providing an overview of state of-the-art research in on-chip networks. We believe that an overview that teaches both fundamental concepts and highlights state-of-the-art designs will be of great value to both graduate students and industry engineers. While not an exhaustive text, we hope to illuminate fundamental concepts for the reader as well as identify trends and gaps in on-chip network research.

论文CFnet中的预训练网络文件，包含10个训练好的mat网络文件。

problem solution for computer networks(5th edition) written by ANDREW S.TANENBAUM)

Ebook - WIRELESS SENSOR NETWORKS A Networking Perspective

Welcome to Long Short-Term Memory Networks With Python. Long Short-Term Memory (LSTM) recurrent neural networks are one of the most interesting types of deep learning at the moment. They have been used to demonstrate world-class results in complex problem domains such as language translation, automatic image captioning, and text generation. LSTMs are very di↵erent to other deep learning techniques, such as Multilayer Perceptrons (MLPs) and Convolutional Neural Networks (CNNs), in that they are designed specifically for sequence prediction problems. I designed this book for you to rapidly discover what LSTMs are, how they work, and how you can bring this important technology to your own sequence prediction problems.

数据网络 data networks 中文版 第三章/ (美) Dimitri Bertsekas, Robert Gallager著 ;（照片完整版）非PDF

Michael Nielsen的⼀本书兼顾理论和动⼿实践的书。讲解了神经网络和深度学习的众多核心概念，也包含了作者对深度学习的深刻理解和透彻思考，并附代码实例。非常适合初学者入门。