In order to improve measurement accuracy of moving target signals, an automatic target recognition model of moving target signals was established based on empirical mode decomposition(EMD) and support vector machine(S...In order to improve measurement accuracy of moving target signals, an automatic target recognition model of moving target signals was established based on empirical mode decomposition(EMD) and support vector machine(SVM). Automatic target recognition process on the nonlinear and non-stationary of Doppler signals of military target by using automatic target recognition model can be expressed as follows. Firstly, the nonlinearity and non-stationary of Doppler signals were decomposed into a set of intrinsic mode functions(IMFs) using EMD. After the Hilbert transform of IMF, the energy ratio of each IMF to the total IMFs can be extracted as the features of military target. Then, the SVM was trained through using the energy ratio to classify the military targets, and genetic algorithm(GA) was used to optimize SVM parameters in the solution space. The experimental results show that this algorithm can achieve the recognition accuracies of 86.15%, 87.93%, and 82.28% for tank, vehicle and soldier, respectively.展开更多
Automatic mode-locking techniques,the integration of intelligent technologies with nonlinear optics offers the promise of on-demand intelligent control,potentially overcoming the inherent limitations of traditional ul...Automatic mode-locking techniques,the integration of intelligent technologies with nonlinear optics offers the promise of on-demand intelligent control,potentially overcoming the inherent limitations of traditional ultrafast pulse generation that have predominantly suffered from the instability and suboptimality of open-loop manual tuning.The advancements in intelligent algorithm-driven automatic mode-locking techniques primarily are explored in this review,which also revisits the fundamental principles of nonlinear optical absorption,and examines the evolution and categorization of conventional mode-locking techniques.The convergence of ultrafast pulse nonlinear interactions with intelligent technologies has intricately expanded the scope of ultrafast photonics,unveiling considerable potential for innovation and catalyzing new waves of research breakthroughs in ultrafast photonics and nonlinear optics characters.展开更多
基金Projects(61471370,61401479)supported by the National Natural Science Foundation of China
文摘In order to improve measurement accuracy of moving target signals, an automatic target recognition model of moving target signals was established based on empirical mode decomposition(EMD) and support vector machine(SVM). Automatic target recognition process on the nonlinear and non-stationary of Doppler signals of military target by using automatic target recognition model can be expressed as follows. Firstly, the nonlinearity and non-stationary of Doppler signals were decomposed into a set of intrinsic mode functions(IMFs) using EMD. After the Hilbert transform of IMF, the energy ratio of each IMF to the total IMFs can be extracted as the features of military target. Then, the SVM was trained through using the energy ratio to classify the military targets, and genetic algorithm(GA) was used to optimize SVM parameters in the solution space. The experimental results show that this algorithm can achieve the recognition accuracies of 86.15%, 87.93%, and 82.28% for tank, vehicle and soldier, respectively.
基金National Natural Science Foundation of China(42406182)the China Postdoctoral Science Foundation Funded Project(GZC20232979)+4 种基金the National Natural Science Foundation of China(62205091)the China Postdoctoral Science Foundation Funded Project(2022M710983)HeiLongJiang Postdoctoral Foundation(LBH-Z22201)Supported by the Fundamental Research Foundation for Universities of Heilongjiang Province:2022-KYYWF-0121the China Postdoctoral Science Foundation Funded Project(2023TQ0369).
文摘Automatic mode-locking techniques,the integration of intelligent technologies with nonlinear optics offers the promise of on-demand intelligent control,potentially overcoming the inherent limitations of traditional ultrafast pulse generation that have predominantly suffered from the instability and suboptimality of open-loop manual tuning.The advancements in intelligent algorithm-driven automatic mode-locking techniques primarily are explored in this review,which also revisits the fundamental principles of nonlinear optical absorption,and examines the evolution and categorization of conventional mode-locking techniques.The convergence of ultrafast pulse nonlinear interactions with intelligent technologies has intricately expanded the scope of ultrafast photonics,unveiling considerable potential for innovation and catalyzing new waves of research breakthroughs in ultrafast photonics and nonlinear optics characters.
