jive networks

Deep Learning SpecializationWunda recently launched a series of courses on deep learning in Coursera with Deeplearning.ai, which is more practical compared to the previous machine learning course. The operating language also has MATLAB changed to Python to be more fit to the current trend. A study note on this series of courses will be made here.The deep learning specialization is divided into five courses, namely: Neural Networks and deep learning,im

How should we set wireless network technology? How does IPV6 affect wireless networks? The following articles unveil the mysteries of us. 1. Introduction 3G network operators hope to provide a large number of application services for potential customers, including traditional voice services and unimaginable services. 3G networks can handle a large amount of traffic needs, which may lead to the implementatio

Wired networks have always been a frequent network type for home and enterprise users. However, with the popularity of wireless networks, wired networks gradually expose their inevitable drawbacks: a large number of cabling and line change projects; lines are prone to damage; nodes in the network cannot be moved. In particular, when connecting distant nodes, it i

management, mobility management and call control functions, including location update, authentication, call, paging, switching, etc. The terminal and network are identified by PSNumber (equivalent to IMSI in GSM). The wireless network includes the base station and the base station controller, connect to the core network through the interface. ZTE's PHS System is a mobile network system based on the GSM network architecture, including MSC/VLR (IGW) and HLR. The A interface evolved from the gsm b

Although, at present, 3G wireless communication networks have not been applied to every mobile user as expected. However, the author believes that this is only a matter of time, and does not prevent us from looking forward to the bright future of 3G wireless communication networks. 3G has set a new goal for itself-digital intelligence for our lives. China Unicom is setting a new goal for 3G business applica

Definition of energy efficiency in communication networks and its value for energy-saving management across the network Improving the energy efficiency of communication networks (EE) is an important means to improve the profitability of operators. The energy efficiency indicators are further divided into TEE and IEE) it can better adapt to the organization model of Maintenance Management for telecom operat

Label: style blog HTTP Io SP strong on 2014 Preface: Keep your style consistent. Before you officially start writing, start with a long talk. There are too many books and articles about neural networks, so I am not allowed to talk about them in a word that is too arrogant. I try to write a little more information. After reading this article, I can have a general understanding of neural networks and have so

Original: https://medium.com/learning-new-stuff/how-to-learn-neural-networks-758b78f2736e#.ly5wpz44dThe second post in a series of me trying to learn something new over a short period of time. The first time consisted of learning how to does machine learning in a week.This time I ' ve tried to learn neural networks. While I didn ' t manage to does it within a week, due to various reasons, I did get a basic

1. Introduction Automatic Switching Optical Network (ASON) technology has been accumulating and improving after years of development. For most carriers in China, Traditional transmission networks already have a large scale. How to introduce ASON technology more rationally to achieve stable evolution of transmission networks is the main issue discussed in this article. 2. Introduction of ASON technology At p

Broadband access networks are worth learning. Here we mainly introduce the Network Positioning of broadband access servers and the system requirements of broadband access servers, including the extended functions of broadband access servers. With the increasing process of broadband data networks, Wide Area Network broadband access technology, represented by xDSL, HFCs, and even optical fiber LAN, has develo

In order to adapt to the rapid development of data services represented by IP Services and the trend that the data business volume will exceed or greatly exceed the voice business volume; to adapt to the changes in network traffic distribution caused by customer-server and other application methods, as well as the unique self-similarity of IP Services and the asymmetry of sending and receiving, to support an endless stream of online applications, all countries in the world are exploring and expe

in multiple adapters or interfacesEthtool-s Displaying network statisticsEthtool Speed netstatDiscover the most useful and common Linux commands for host connections. You can use "netstat-g" to query all multicast groups (networks) that the host subscribes toNetstat-nap | grep Port will show the process ID of the application using that portNetstat-a or Netstat–all will display all connections that include TCP and UDPNetstat–tcp or netstat–t will disp

3D Graph Neural Networks for RGBD Semantic segmentation2018-04-13 19:19:481. Introduction:With the development of depth sensors, RGBD semantic segmentation is applied to many problems, such as virtual reality, robot, human-computer interaction and so on. Compared with the existing 2D semantic segmentation, RGBD semantic segmentation can use real-world geometric information to assist segmentation by exploring depth information. As shown in the normal 2

Basic informationSection Two, Water divisionAutomatic water-body segmentation from high-resolution satellite Images via deep NetworksNotes starting point Water Division is the basic task of remote sensing. The traditional method relies on spectra and can only handle low resolution images. And the resolution of the picture, contains more details. The robustness of the method is tested by the data obtained from different data sensors. The main innovation point Propos

! Each function you'll implement'll have detailed instructions that'll walk you through the steps needed:convolution Functions, Including:zero Padding convolve window convolution forward convolution backward (optional) pooling functions, Including:pooling forward Create Mask distribute value pooling backward (optional) This notebook would ask you for implement these functions from scratch in numpy. In the next notebook, you'll use the TensorFlow equivalents of this functions to build the followi

follows: The first step is to perform feature map selection for the conv4-3 and conv5-3 layers of the Vgg network for a given target, which is to select the most relevant feature maps, the specific reason being to construct a regular objective function of the L1 norm. In the second step, based on the feature maps of Conv5-3, a universal network gnet is constructed to capture the category information of the target. The third step, based on the conv4-3 feature maps, constructs a specific network

. The artificial intelligence technology in game programming (serial one) Introducing neural networks in normal language(Neural Networks in Plain 中文版) Because we do not have a good understanding of the brain, we often try to use the latest technology as a model to explain it. When I was a child, we all believed that the brain was a telephone switch. (Otherwise, what else could it be?) I also saw

Application examples of RNN--a language model based on RNN Now, let's introduce a model based on the RNN language. We first input the word into the recurrent neural network, each input word, the recurrent neural network output so far, the next most likely word. For example, when we enter in turn: I was late for school yesterday. The output of the neural network is shown in the following figure: where S and e are two special words that represent the beginning and the end of a sequence, resp

machine translation) system, which uses current state-of-the-art training techniques to achieve the greatest increase in machine translation quality so far. For details of all our findings, please refer to our paper "Google's neural machine translation system:bridging the Gap between Human and machine translation" (see end) [1]. A few years ago, we started using recurrent neural networks (rnn:recurrent neural Ne