Coding theoryElectrical Engineering Fundamentals of Convolutional Coding A volume in the IEEE Press Series on Digital and Mobile Communication John B. Anderson, Series Editor Convolutional codes, among the main error control codes, are routinely used in applications for mobile telephony, satellite ...
出版社: Institute of Electrical and Electronics Engineers, 摘要: Electrical Engineering Fundamentals of Convolutional Coding A volume in the IEEE Press Series on Digital and Mobile Communication John B. Anderson, Series Editor Convolutional codes, among the main error control codes, are routinely used ...
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The Theory of Error Correcting Codes, F. J. MacWilliams. N. J. A. Sloane, 1977. • Fundamentals of Convolutional Coding, R. Johannesson. received. One says it is a single error correcting code. (2) W. Cary Huffman and Vera Pless, Fundamentals of Error"Correcting Codes, Cambridge. ...
Hyena Hierarchy: Towards Larger Convolutional Language Models (Paper) Hyena Hierarchy: Towards Larger Convolutional Language Models Hungry Hungry Hippos: Towards Language Modeling with State Space Models What is the difference between encoders, decoders, and encoder-decoder architectures in LLMs? Understand...
12.6 Appendix: App12.pdf at www.wiley.com/go/molisch/wireless3e 277 13 Channel Coding and Information Theory 279 13.1 Fundamentals of Coding and Information Theory 279 13.2 Block Codes 284 13.3 Convolutional Codes 288 13.4 Trellis Coded Modulation 297 13.5 Bit Interleaved Coded Modulation...
◮BinaryCodes:Block,Convolutional,LDPC,Concatenated,etc. ◮ManysolutionsforRc<1basedonbinarysignaling(|X|=2,e.g.,FSK, BPSK)+Channelcode(withrate0≤R≤1). ◮Excellentsummaryofthesesolutionsin[CF07,FU98] S.Chung,G.D.Forney,Jr.,T.J.Richardson,andR.L.Urbanke,“Onthedesignoflow-density ...
[130] developed an active placement method without closed-loop control by training multiple convolutional neural networks, thereby significantly reducing the time consumption of active assembly. In general, the combination of vision and deep neural networks helps reduce manual labor while maintaining the ...
Finally, the fully connected layer, typically a DNN, performs classification on the features extracted by the series of convolutional and pooling layers. An example architecture of DCNN is illustrated in Figure 2. Features learned at different layers of DCNN correspond to different levels of ...
《Fundamentals of Robotic Mechanical Systems Theory, Methods, and Algorithms》第四版,原文作者Jorge Angeles,主要讲述机器人机械系统原理理论方法和算法。