Introduction jSMPP is a java implementation (SMPP API) of the SMPP protocol (currently supports SMPP v3.4). It provides interfaces to communicate with a Message Center or an ESME (External Short Message Entity) and is able to handle traffic of 3000-5000 messages per second. jSMPP is not a high-level library. People looking for a quick way to get started with SMPP may be better of using an abstraction Layer such as the Apache Camel SMPP component: http://camel.apache.org/smpp.html Travis-CI status: History The project started on Google Code: http://code.google.com/p/jsmpp/ It was maintained by uudashr on Github until 2013. It is now a community project maintained at http://jsmpp.org Release procedure mvn deploy -DperformRelease=true -Durl=https://oss.sonatype.org/service/local/staging/deploy/maven2/ -DrepositoryId=sonatype-nexus-staging -Dgpg.passphrase=<yourpassphrase> log in here: https://oss.sonatype.org click the 'Staging Repositories' link select the repository and click close select the repository and click release License Copyright (C) 2007-2013, Nuruddin Ashr uudashr@gmail.com Copyright (C) 2012-2013, Denis Kostousov denis.kostousov@gmail.com Copyright (C) 2014, Daniel Pocock http://danielpocock.com Copyright (C) 2016, Pim Moerenhout pim.moerenhout@gmail.com This project is licensed under the Apache Software License 2.0.
上传时间： 2019-01-25
上传用户：dragon_longer
pcie3.0标准规范 1. INTRODUCTION 2. TRANSACTION Layer SPECIFICATION 3. DATA LINK Layer SPECIFICATION 4. PHYSICAL Layer SPECIFICATION 5. POWER MANAGEMENT 6. SYSTEM ARCHITECTURE 7. SOFTWARE INITIALIZATION AND CONFIGURATION
标签： pcie3
上传时间： 2019-07-05
上传用户：bingshi
This introduction takes a visionary look at ideal cognitive radios (CRs) that inte- grate advanced software-defined radios (SDR) with CR techniques to arrive at radios that learn to help their user using computer vision, high-performance speech understanding, global positioning system (GPS) navigation, sophisticated adaptive networking, adaptive physical Layer radio waveforms, and a wide range of machine learning processes.
标签： Technology Cognitive Radio
上传时间： 2020-05-26
上传用户：shancjb
It is commonly accepted today that optical fiber communications have revolutionized telecommunications. Indeed, dramatic changes have been induced in the way we interact with our relatives, friends, and colleagues: we retrieve information, we entertain and educate ourselves, we buy and sell, we organize our activities, and so on, in a long list of activities. Optical fiber systems initially allowed for a significant curb in the cost of transmission and later on they sparked the process of a major rethinking regarding some, generation-old, telecommunication concepts like the (OSI)-Layer definition, the lack of cross-Layer dependency, the oversegmentation and overfragmentation of telecommunica- tions networks, and so on.
上传时间： 2020-05-27
上传用户：shancjb
The writing of this book was prompted by two main developments in wireless communications in the past decade. First is the huge surge of research activities in physical-Layer wireless communication theory. While this has been a subject of study since the 60’s, recent developments in the field, such as opportunistic and multi-input multi-output (MIMO) communication techniques, have brought completely new per- spectives on how to communicate over wireless channels.
标签： Communication Fundamentals Wireless of
上传时间： 2020-05-27
上传用户：shancjb
Multi-carrier modulation‚ Orthogonal Frequency Division Multi- plexing (OFDM) particularly‚ has been successfully applied to a wide variety of digital communications applications over the past several years. Although OFDM has been chosen as the physical Layer standard for a diversity of important systems‚ the theory‚ algorithms‚ and implementation techniques remain subjects of current interest. This is clear from the high volume of papers appearing in technical journals and conferences.
标签： COMMUNICATIONS MULTI-CARRIER DIGITAL
上传时间： 2020-05-31
上传用户：shancjb
The investigation of the propagation channel is becoming more and more important in mod- ern wireless communication. The demand for spectral efficiency motivates exploitation of all channels that can possibly be used for communications. Nowadays, a common trend for designing physical Layer algorithms is to adapt the transceiving strategy, either by maximizing the diversity gains or by utilizing the coherence of the channels to improve the signal-to-noise power ratio.
标签： Characterization Propagation Channel
上传时间： 2020-05-31
上传用户：shancjb
Wireless communications has become a field of enormous scientific and economic interest. Recent success stories include 2G and 3G cellular voice and data services (e.g., GSM and UMTS), wireless local area networks (WiFi/IEEE 802.11x), wireless broadband access (WiMAX/IEEE 802.16x), and digital broadcast systems (DVB, DAB, DRM). On the physical Layer side, traditional designs typically assume that the radio channel remains constant for the duration of a data block. However, researchers and system designers are increasingly shifting their attention to channels that may vary within a block. In addition to time dispersion caused by multipath propagation, these rapidly time-varying channels feature frequency dispersion resulting from the Doppler effect. They are, thus, often referred to as being “doubly dispersive.”
标签： Time-Varying Channels
上传时间： 2020-06-01
上传用户：shancjb
stract With global drivers such as better energy consumption, energy efficiency and reduction of greenhouse gases, CO 2 emission reduction has become key in every Layer of the value chain. Power Electronics has definitely a role to play in these thrilling challenges. From converters down to compound semiconductors, innovation is leading to breakthrough technologies. Wide BandGap, Power Module Packaging, growth of Electric Vehicle market will game change the overall power electronic industry and supply chain. In this presentation we will review power electronics trends, from technologies to markets.
标签： Electronics Materials Power WBG for
上传时间： 2020-06-07
上传用户：shancjb
Recent work has shown that convolutional networks can be substantially deeper, more accurate, and efficient to train if they contain shorter connections between Layers close to the input and those close to the output. In this paper, we embrace this observation and introduce the Dense Convo- lutional Network (DenseNet), which connects each Layer to every other Layer in a feed-forward fashion.
标签： Convolutional Connected Networks Densely
上传时间： 2020-06-10
上传用户：shancjb
