C波段無(wú)線電信號(hào)智能分類(lèi)識(shí)別研究.pdf

1、分類(lèi)號(hào)分類(lèi)號(hào)O45學(xué)校代碼學(xué)校代碼10233密級(jí)密級(jí)公開(kāi)學(xué)號(hào)學(xué)號(hào)10233120810碩士研究生學(xué)位論文題目：目：C波段無(wú)線電信號(hào)智能分類(lèi)識(shí)別研究學(xué)科門(mén)類(lèi)：學(xué)科門(mén)類(lèi)：理學(xué)一級(jí)學(xué)科：一級(jí)學(xué)科：物理學(xué)二級(jí)學(xué)科二級(jí)學(xué)科：無(wú)線電物理研究方向研究方向::無(wú)線電信號(hào)系統(tǒng)的辨識(shí)與處理研究生::于成龍指導(dǎo)教師指導(dǎo)教師::趙寶江教授答辯日期：答辯日期：2015年6月3日AbstractAbstractRadiospectrumresourcesisani

2、mptantnationalstrategicresource.Radiospectrumresourcesarenotinexhaustiblepublicresourcesitslimitedincreasinglyprominent.Thehumandemfradiospectrumresourcesisrapidlyexpingcompetitivevariousradiotechnologiesapplicationsbeco

3、memeintensesothatthescarcityofradiospectrumresourcescontinuetoincreasenotallkindsofinterferencesignalsegmentincreased.Indertobetterradiospectrummanagementmonitingthroughtechnicalmeanstomonittheradiosignalsofintelligentcl

4、assificationrecognitionontheshowisextremelyimptantfaccurateclassificationofradiosignalsmepracticalsignificance.InthispaperusingdifferentfeatureextractionmethodsfCbradiosignalfeatureextractionusebackpropagationlearningalg

5、ithmtodointelligentclassifiertoclassifyCbradiosignalrecognition.Themaincontentsareasfollows:1.IntroductionWhatisCbradiosignalsdescribestheprincipalcomponentsanalysisBackpropagationlearningalgithmdesignprinciplesmathemati

6、calmodels.2.StudyoffeatureextractionmethodsduetothehugeamountofdataradiosignaldataofhighdimensionalityweuseamethodbasedonprincipalcomponentsanalysisfrequencydomainfeaturesstatisticacteristicsoffeatureextractionofCbradios

7、ignalfeatureextraction.3.usingbackpropagationlearningalgithmasanintelligentclassifiertoclassifytheidentificationoftheCbradiosignalfingtheparametersofbackpropagationlearningalgithmisanalyzedtheuseofdifferentmethodsoffeatu