In modern electromagnetic environment, radar emitter signal recognition is an important research topic. On the basis of multi-resolution wavelet analysis, an adaptive radar emitter signal recognition method based on m...In modern electromagnetic environment, radar emitter signal recognition is an important research topic. On the basis of multi-resolution wavelet analysis, an adaptive radar emitter signal recognition method based on multi-scale wavelet entropy feature extraction and feature weighting was proposed. With the only priori knowledge of signal to noise ratio(SNR), the method of extracting multi-scale wavelet entropy features of wavelet coefficients from different received signals were combined with calculating uneven weight factor and stability weight factor of the extracted multi-dimensional characteristics. Radar emitter signals of different modulation types and different parameters modulated were recognized through feature weighting and feature fusion. Theoretical analysis and simulation results show that the presented algorithm has a high recognition rate. Additionally, when the SNR is greater than-4 d B, the correct recognition rate is higher than 93%. Hence, the proposed algorithm has great application value.展开更多
The neuromorphic systems for sound perception is under highly demanding for the future bioinspired electronics and humanoid robots.However,the sound perception based on volume,tone and timbre remains unknown.Herein,or...The neuromorphic systems for sound perception is under highly demanding for the future bioinspired electronics and humanoid robots.However,the sound perception based on volume,tone and timbre remains unknown.Herein,organic optoelectronic synapses(OOSs)are constructed for unprecedented sound recognition.The volume,tone and timbre of sound can be regulated appropriately by the input signal of voltages,frequencies and light intensities of OOSs,according to the amplitude,frequency,and waveform of the sound.The quantitative relation between recognition factor(ζ)and postsynaptic current(I=I_(light)−I_(dark))is established to achieve sound perception.Interestingly,the bell sound for University of Chinese Academy of Sciences is recognized with an accuracy of 99.8%.The mechanism studies reveal that the impedance of the interfacial layers play a critical role in the synaptic performances.This contribution presents unprecedented artificial synapses for sound perception at hardware levels.展开更多
基金Project(61301095)supported by the National Natural Science Foundation of ChinaProject(QC2012C070)supported by Heilongjiang Provincial Natural Science Foundation for the Youth,ChinaProjects(HEUCF130807,HEUCFZ1129)supported by the Fundamental Research Funds for the Central Universities of China
文摘In modern electromagnetic environment, radar emitter signal recognition is an important research topic. On the basis of multi-resolution wavelet analysis, an adaptive radar emitter signal recognition method based on multi-scale wavelet entropy feature extraction and feature weighting was proposed. With the only priori knowledge of signal to noise ratio(SNR), the method of extracting multi-scale wavelet entropy features of wavelet coefficients from different received signals were combined with calculating uneven weight factor and stability weight factor of the extracted multi-dimensional characteristics. Radar emitter signals of different modulation types and different parameters modulated were recognized through feature weighting and feature fusion. Theoretical analysis and simulation results show that the presented algorithm has a high recognition rate. Additionally, when the SNR is greater than-4 d B, the correct recognition rate is higher than 93%. Hence, the proposed algorithm has great application value.
基金supported by the NSFC(51925306 and 21774130)National Key R&D Program of China(2018FYA 0305800)+2 种基金Key Research Program of the Chinese Academy of Sciences(XDPB08-2)the Strategic Priority Research Program of Chinese Academy of Sciences(XDB28000000)University of Chinese Academy of Sciences.
文摘The neuromorphic systems for sound perception is under highly demanding for the future bioinspired electronics and humanoid robots.However,the sound perception based on volume,tone and timbre remains unknown.Herein,organic optoelectronic synapses(OOSs)are constructed for unprecedented sound recognition.The volume,tone and timbre of sound can be regulated appropriately by the input signal of voltages,frequencies and light intensities of OOSs,according to the amplitude,frequency,and waveform of the sound.The quantitative relation between recognition factor(ζ)and postsynaptic current(I=I_(light)−I_(dark))is established to achieve sound perception.Interestingly,the bell sound for University of Chinese Academy of Sciences is recognized with an accuracy of 99.8%.The mechanism studies reveal that the impedance of the interfacial layers play a critical role in the synaptic performances.This contribution presents unprecedented artificial synapses for sound perception at hardware levels.
