Nonlinear Transform Source-Channel Coding for Semantic Communications

In this paper, we propose a class of high-efficiency deep joint source-channel coding methods that can closely adapt to the source distribution under the nonlinear transform, it can be collected under the name nonlinear transform source-channel coding (NTSCC). In the considered model, the transmitte...

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Vydané v:	IEEE journal on selected areas in communications Ročník 40; číslo 8; s. 2300 - 2316
Hlavní autori:	Dai, Jincheng, Wang, Sixian, Tan, Kailin, Si, Zhongwei, Qin, Xiaoqi, Niu, Kai, Zhang, Ping
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.08.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Channel coding Codec Coding Design optimization Digital transmission Encoding Entropy Feature extraction Image coding Image quality joint source-channel coding Nonlinear analysis nonlinear transform perceptual loss rate-distortion Representations Semantic communications Semantics Systems design Transforms
ISSN:	0733-8716, 1558-0008
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