Signal modulation identification algorithm of time convolution network with attention mechanism
The embodiment of the invention discloses a signal modulation recognition algorithm of a time convolution network with an attention mechanism. According to the embodiment of the invention, to-be-identified modulation signal data is acquired; sampling the modulation signal data to be identified, and...
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| creator | TANG XIAOGANG TAO RAN LI JIONG GAO MINGHUI REN YANJIE ZHANG BINQUAN HUAN HAO |
| description | The embodiment of the invention discloses a signal modulation recognition algorithm of a time convolution network with an attention mechanism. According to the embodiment of the invention, to-be-identified modulation signal data is acquired; sampling the modulation signal data to be identified, and determining a modulation signal sequence to be identified; and inputting the modulation signal sequence to be identified into a pre-trained time convolution network model combined with an attention mechanism, and determining a target modulation mode of the modulation signal sequence to be identified. According to the method, the target modulation mode is determined by adopting the time convolution network module combined with the attention mechanism, the modulation mode identification accuracy can be improved, the redundant calculation amount is reduced, and the operation time is shortened.
本发明实施例公开了一种具有注意力机制时间卷积网络的信号调制识别算法。本发明实施例通过获取待识别调制信号数据；将所述待识别调制信号数据进行采样处理，确定待识别调制信号序列；将所述待识别调制信号序列输入到预先训练的结合注意力机制的时间卷积网络模型，确定出所 |
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本发明实施例公开了一种具有注意力机制时间卷积网络的信号调制识别算法。本发明实施例通过获取待识别调制信号数据；将所述待识别调制信号数据进行采样处理，确定待识别调制信号序列；将所述待识别调制信号序列输入到预先训练的结合注意力机制的时间卷积网络模型，确定出所</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; ELECTRIC COMMUNICATION TECHNIQUE ; ELECTRICITY ; HANDLING RECORD CARRIERS ; PHYSICS ; PRESENTATION OF DATA ; RECOGNITION OF DATA ; RECORD CARRIERS ; TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION</subject><creationdate>2022</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20220909&DB=EPODOC&CC=CN&NR=115034255A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25543,76294</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20220909&DB=EPODOC&CC=CN&NR=115034255A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>TANG XIAOGANG</creatorcontrib><creatorcontrib>TAO RAN</creatorcontrib><creatorcontrib>LI JIONG</creatorcontrib><creatorcontrib>GAO MINGHUI</creatorcontrib><creatorcontrib>REN YANJIE</creatorcontrib><creatorcontrib>ZHANG BINQUAN</creatorcontrib><creatorcontrib>HUAN HAO</creatorcontrib><title>Signal modulation identification algorithm of time convolution network with attention mechanism</title><description>The embodiment of the invention discloses a signal modulation recognition algorithm of a time convolution network with an attention mechanism. According to the embodiment of the invention, to-be-identified modulation signal data is acquired; sampling the modulation signal data to be identified, and determining a modulation signal sequence to be identified; and inputting the modulation signal sequence to be identified into a pre-trained time convolution network model combined with an attention mechanism, and determining a target modulation mode of the modulation signal sequence to be identified. According to the method, the target modulation mode is determined by adopting the time convolution network module combined with the attention mechanism, the modulation mode identification accuracy can be improved, the redundant calculation amount is reduced, and the operation time is shortened.
本发明实施例公开了一种具有注意力机制时间卷积网络的信号调制识别算法。本发明实施例通过获取待识别调制信号数据；将所述待识别调制信号数据进行采样处理，确定待识别调制信号序列；将所述待识别调制信号序列输入到预先训练的结合注意力机制的时间卷积网络模型，确定出所</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC COMMUNICATION TECHNIQUE</subject><subject>ELECTRICITY</subject><subject>HANDLING RECORD CARRIERS</subject><subject>PHYSICS</subject><subject>PRESENTATION OF DATA</subject><subject>RECOGNITION OF DATA</subject><subject>RECORD CARRIERS</subject><subject>TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2022</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNjEsOgkAQRNm4MOod2gOYiMgBDNG4cqP7SWfogQ4z0wQaub7j5wCuKlX1qpaZuXMT0UOQevKoLBG4pqjs2H4t-kYG1jaAOFAOBFbiU_z0aSPpLEMHcyIAVd_TFAeyLUYewzpbOPQjbX66yraX86O67qgXQ2OPltKFqW55Xu6L46EsT8U_zAsurD46</recordid><startdate>20220909</startdate><enddate>20220909</enddate><creator>TANG XIAOGANG</creator><creator>TAO RAN</creator><creator>LI JIONG</creator><creator>GAO MINGHUI</creator><creator>REN YANJIE</creator><creator>ZHANG BINQUAN</creator><creator>HUAN HAO</creator><scope>EVB</scope></search><sort><creationdate>20220909</creationdate><title>Signal modulation identification algorithm of time convolution network with attention mechanism</title><author>TANG XIAOGANG ; TAO RAN ; LI JIONG ; GAO MINGHUI ; REN YANJIE ; ZHANG BINQUAN ; HUAN HAO</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN115034255A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2022</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC COMMUNICATION TECHNIQUE</topic><topic>ELECTRICITY</topic><topic>HANDLING RECORD CARRIERS</topic><topic>PHYSICS</topic><topic>PRESENTATION OF DATA</topic><topic>RECOGNITION OF DATA</topic><topic>RECORD CARRIERS</topic><topic>TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION</topic><toplevel>online_resources</toplevel><creatorcontrib>TANG XIAOGANG</creatorcontrib><creatorcontrib>TAO RAN</creatorcontrib><creatorcontrib>LI JIONG</creatorcontrib><creatorcontrib>GAO MINGHUI</creatorcontrib><creatorcontrib>REN YANJIE</creatorcontrib><creatorcontrib>ZHANG BINQUAN</creatorcontrib><creatorcontrib>HUAN HAO</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>TANG XIAOGANG</au><au>TAO RAN</au><au>LI JIONG</au><au>GAO MINGHUI</au><au>REN YANJIE</au><au>ZHANG BINQUAN</au><au>HUAN HAO</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Signal modulation identification algorithm of time convolution network with attention mechanism</title><date>2022-09-09</date><risdate>2022</risdate><abstract>The embodiment of the invention discloses a signal modulation recognition algorithm of a time convolution network with an attention mechanism. According to the embodiment of the invention, to-be-identified modulation signal data is acquired; sampling the modulation signal data to be identified, and determining a modulation signal sequence to be identified; and inputting the modulation signal sequence to be identified into a pre-trained time convolution network model combined with an attention mechanism, and determining a target modulation mode of the modulation signal sequence to be identified. According to the method, the target modulation mode is determined by adopting the time convolution network module combined with the attention mechanism, the modulation mode identification accuracy can be improved, the redundant calculation amount is reduced, and the operation time is shortened.
本发明实施例公开了一种具有注意力机制时间卷积网络的信号调制识别算法。本发明实施例通过获取待识别调制信号数据；将所述待识别调制信号数据进行采样处理，确定待识别调制信号序列；将所述待识别调制信号序列输入到预先训练的结合注意力机制的时间卷积网络模型，确定出所</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC COMMUNICATION TECHNIQUE ELECTRICITY HANDLING RECORD CARRIERS PHYSICS PRESENTATION OF DATA RECOGNITION OF DATA RECORD CARRIERS TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION |
| title | Signal modulation identification algorithm of time convolution network with attention mechanism |
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