Enhancing resonance frequency of strong optical studied. Resonance frequency is increased from technique. We experimentally demonstrate that injection-locked semiconductor lasers is experimentally 4.1 to 53.9 GHz by t...Enhancing resonance frequency of strong optical studied. Resonance frequency is increased from technique. We experimentally demonstrate that injection-locked semiconductor lasers is experimentally 4.1 to 53.9 GHz by the optical injection locking （OIL） resonance frequency is strictly equal to the frequency spacing between the cavity modes of the master and slave lasers under strong OIL condition. This result provides valuable information to improve OIL theory.展开更多
Hypersonic Glide Vehicles(HGVs)are advanced aircraft that can achieve extremely high speeds(generally over 5 Mach)and maneuverability within the Earth's atmosphere.HGV trajectory prediction is crucial for effectiv...Hypersonic Glide Vehicles(HGVs)are advanced aircraft that can achieve extremely high speeds(generally over 5 Mach)and maneuverability within the Earth's atmosphere.HGV trajectory prediction is crucial for effective defense planning and interception strategies.In recent years,HGV trajectory prediction methods based on deep learning have the great potential to significantly enhance prediction accuracy and efficiency.However,it's still challenging to strike a balance between improving prediction performance and reducing computation costs of the deep learning trajectory prediction models.To solve this problem,we propose a new deep learning framework(FECA-LSMN)for efficient HGV trajectory prediction.The model first uses a Frequency Enhanced Channel Attention(FECA)module to facilitate the fusion of different HGV trajectory features,and then subsequently employs a Light Sampling-oriented Multi-Layer Perceptron Network(LSMN)based on simple MLP-based structures to extract long/shortterm HGV trajectory features for accurate trajectory prediction.Also,we employ a new data normalization method called reversible instance normalization(RevIN)to enhance the prediction accuracy and training stability of the network.Compared to other popular trajectory prediction models based on LSTM,GRU and Transformer,our FECA-LSMN model achieves leading or comparable performance in terms of RMSE,MAE and MAPE metrics while demonstrating notably faster computation time.The ablation experiments show that the incorporation of the FECA module significantly improves the prediction performance of the network.The RevIN data normalization technique outperforms traditional min-max normalization as well.展开更多
The flexible materials exhibit more favorable properties than most rigid substrates in flexibility,weight saving,mechanical reliability,and excellent environmental toughness.Particularly,flexible graphene film with un...The flexible materials exhibit more favorable properties than most rigid substrates in flexibility,weight saving,mechanical reliability,and excellent environmental toughness.Particularly,flexible graphene film with unique mechanical properties was extensively explored in high frequency devices.Herein,we report the characteristics of structure and magnetic properties at high frequency of Co2FeAl thin film with different thicknesses grown on flexible graphene substrate at room temperature.The exciting finding for the columnar structure of Co2FeAl thin film lays the foundation for excellent high frequency property of Co2FeAl/flexible graphene structure.In-plane magnetic anisotropy field varying with increasing thickness of Co2FeAl thin film can be obtained by measurement of ferromagnetic resonance,which can be ascribed to the enhancement of crystallinity and the increase of grain size.Meanwhile,the resonance frequency which can be achieved by the measurement of vector network analyzer with the microstrip method increases with increasing thickness of Co2FeAl thin film.Moreover,in our case with graphene film,the resonance magnetic field is quite stable though folded for twenty cycles,which demonstrates that good flexibility of graphene film and the stability of high frequency magnetic property of Co2FeAl thin film grown on flexible graphene substrate.These results are promising for the design of microwave devices and wireless communication equipment.展开更多
Various ion sources are key components to prepare functional coatings,such as diamond-like carbon(DLC)films.In this article,we present our trying of surface modification on basis of Si-incorporation diamond-like carbo...Various ion sources are key components to prepare functional coatings,such as diamond-like carbon(DLC)films.In this article,we present our trying of surface modification on basis of Si-incorporation diamond-like carbon(Si-DLC)produced by a magnetic field enhanced radio frequency ion source,which is established to get high density plasma with the help of magnetic field.Under proper deposition process,a contact angle of 111°hydrophobic surface was achieved without any surface patterning,where nanostructure SiC grains appeared within the amorphous microstructure.The surface property was influenced by ion flow parameters as well as the resultant surface microstructure.The magnetic field enhanced radio frequency ion source developed in this paper was useful for protective film applications.展开更多
The extraction of the weakly excited anti-symmetric Lamb wave from a submerged thin spherical shell backscattering is very difficult if the carrier frequency of the incident short tone burst is not at its frequency of...The extraction of the weakly excited anti-symmetric Lamb wave from a submerged thin spherical shell backscattering is very difficult if the carrier frequency of the incident short tone burst is not at its frequency of greatest enhancement. Based on a single channel iterative time reversal technique, a method for isolating the subsonic anti-symmetric Lamb wave is proposed in this paper. The approach does not depend on the form function of a thin shell and any other priori knowledge, and it is also robust in the presence of some stochastic noise. Both theoretical and numerical results show that the subsonic anti-symmetric Lamb wave can be identified, even when the carrier frequency of the incident short tone burst is away from the frequency of greatest enhancement. The phenomenon may also be observed even in the case that the subsonic anti-symmetric Lamb wave is submerged in the noise, other than the case with the Signal to Noise Ratio being less than 10 d B, when the amplitude of the noise is comparable with the specular wave. In this paper, each iteration process contains a traditional transmission and time reversal transmission steps. The two steps can automatically compensate the time delay of the subsonic anti-symmetric Lamb wave relative to the specular wave and within-mode dispersion in the forward wave propagation.展开更多
Based on the frequency-domain multimode theoretical model, detailed investigations on the noise characteristic of the semiconductor ring laser （SRL） are first performed in this paper. The comprehensive nonlinear ter...Based on the frequency-domain multimode theoretical model, detailed investigations on the noise characteristic of the semiconductor ring laser （SRL） are first performed in this paper. The comprehensive nonlinear terms related to the third order nonlinear susceptibility Z3 are included in this model; the Langevin noise sources for electric field and carrier density fluctuations are also taken into account. As the injection current increases, the SRL may present several operation regimes. Remarkable and unusual low frequency noise enhancement in the form of a broad low frequency tail extending all the way to the relaxation oscillation peak is observed in any of the operation regimes of SRLs. The influences of the backscattering coefficient on the relative intensity noise （RIN） spectrum in typical operation regimes are investigated in detail.展开更多
Hydrogenated microcrystalline silicon （μc-Si：H） films are fabricated by very high frequency plasma enhanced chemical vapour deposition （VHF-PECVD） at a silane concentration of 7% and a varying total gas flow ra...Hydrogenated microcrystalline silicon （μc-Si：H） films are fabricated by very high frequency plasma enhanced chemical vapour deposition （VHF-PECVD） at a silane concentration of 7% and a varying total gas flow rate （H2＋SiH4）. Relations between the total gas flow rate and the electrical and structural properties as well as deposition rate of the films are studied. The results indicate that with the total gas flow rate increasing the photosensitivity and deposition rate increase, but the crystalline volume fraction （Xc） and dark conductivity decrease. And the intensity of （220） peak first increases then decreases with the increase of the total gas flow rate. The cause for the changes in the structure and deposition rate of the films with the total gas flow rate is investigated using optical emission spectroscopy （OES）.展开更多
Due to the presence of non-stationarities and discontinuities in the audio signal, segmentation and classification of audio signal is a really challenging task. Automatic music classification and annotation is still c...Due to the presence of non-stationarities and discontinuities in the audio signal, segmentation and classification of audio signal is a really challenging task. Automatic music classification and annotation is still considered as a challenging task due to the difficulty of extracting and selecting the optimal audio features. Hence, this paper proposes an efficient approach for segmentation, feature extraction and classification of audio signals. Enhanced Mel Frequency Cepstral Coefficient (EMFCC)-Enhanced Power Normalized Cepstral Coefficients (EPNCC) based feature extraction is applied for the extraction of features from the audio signal. Then, multi-level classification is done to classify the audio signal as a musical or non-musical signal. The proposed approach achieves better performance in terms of precision, Normalized Mutual Information (NMI), F-score and entropy. The PNN classifier shows high False Rejection Rate (FRR), False Acceptance Rate (FAR), Genuine Acceptance rate (GAR), sensitivity, specificity and accuracy with respect to the number of classes.展开更多
This work focuses on enhancing low frequency seismic data using a convolutional neural network trained on synthetic data.Traditional seismic data often lack both high and low frequencies,which are essential for detail...This work focuses on enhancing low frequency seismic data using a convolutional neural network trained on synthetic data.Traditional seismic data often lack both high and low frequencies,which are essential for detailed geological interpretation and various geophysical applications.Low frequency data is particularly valuable for reducing wavelet sidelobes and improving full waveform inversion(FWI).Conventional methods for bandwidth extension include seismic deconvolution and sparse inversion,which have limitations in recovering low frequencies.The study explores the potential of the U-net,which has been successful in other geophysical applications such as noise attenuation and seismic resolution enhancement.The novelty in our approach is that we do not rely on computationally expensive finite difference modelling to create training data.Instead,our synthetic training data is created from individual randomly perturbed events with variations in bandwidth,making it more adaptable to different data sets compared to previous deep learning methods.The method was tested on both synthetic and real seismic data,demonstrating effective low frequency reconstruction and sidelobe reduction.With a synthetic full waveform inversion to recover a velocity model and a seismic amplitude inversion to estimate acoustic impedance we demonstrate the validity and benefit of the proposed method.Overall,the study presents a robust approach to seismic bandwidth extension using deep learning,emphasizing the importance of diverse and well-designed but computationally inexpensive synthetic training data.展开更多
基金supported by the National "973" Program of China(Nos.2012CB315606 and 2010CB328201)
文摘Enhancing resonance frequency of strong optical studied. Resonance frequency is increased from technique. We experimentally demonstrate that injection-locked semiconductor lasers is experimentally 4.1 to 53.9 GHz by the optical injection locking （OIL） resonance frequency is strictly equal to the frequency spacing between the cavity modes of the master and slave lasers under strong OIL condition. This result provides valuable information to improve OIL theory.
文摘Hypersonic Glide Vehicles(HGVs)are advanced aircraft that can achieve extremely high speeds(generally over 5 Mach)and maneuverability within the Earth's atmosphere.HGV trajectory prediction is crucial for effective defense planning and interception strategies.In recent years,HGV trajectory prediction methods based on deep learning have the great potential to significantly enhance prediction accuracy and efficiency.However,it's still challenging to strike a balance between improving prediction performance and reducing computation costs of the deep learning trajectory prediction models.To solve this problem,we propose a new deep learning framework(FECA-LSMN)for efficient HGV trajectory prediction.The model first uses a Frequency Enhanced Channel Attention(FECA)module to facilitate the fusion of different HGV trajectory features,and then subsequently employs a Light Sampling-oriented Multi-Layer Perceptron Network(LSMN)based on simple MLP-based structures to extract long/shortterm HGV trajectory features for accurate trajectory prediction.Also,we employ a new data normalization method called reversible instance normalization(RevIN)to enhance the prediction accuracy and training stability of the network.Compared to other popular trajectory prediction models based on LSTM,GRU and Transformer,our FECA-LSMN model achieves leading or comparable performance in terms of RMSE,MAE and MAPE metrics while demonstrating notably faster computation time.The ablation experiments show that the incorporation of the FECA module significantly improves the prediction performance of the network.The RevIN data normalization technique outperforms traditional min-max normalization as well.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.51901163 and 12104171)the Fundamental Research Funds for the Central Universities(Grant No.2021XXJS025).
文摘The flexible materials exhibit more favorable properties than most rigid substrates in flexibility,weight saving,mechanical reliability,and excellent environmental toughness.Particularly,flexible graphene film with unique mechanical properties was extensively explored in high frequency devices.Herein,we report the characteristics of structure and magnetic properties at high frequency of Co2FeAl thin film with different thicknesses grown on flexible graphene substrate at room temperature.The exciting finding for the columnar structure of Co2FeAl thin film lays the foundation for excellent high frequency property of Co2FeAl/flexible graphene structure.In-plane magnetic anisotropy field varying with increasing thickness of Co2FeAl thin film can be obtained by measurement of ferromagnetic resonance,which can be ascribed to the enhancement of crystallinity and the increase of grain size.Meanwhile,the resonance frequency which can be achieved by the measurement of vector network analyzer with the microstrip method increases with increasing thickness of Co2FeAl thin film.Moreover,in our case with graphene film,the resonance magnetic field is quite stable though folded for twenty cycles,which demonstrates that good flexibility of graphene film and the stability of high frequency magnetic property of Co2FeAl thin film grown on flexible graphene substrate.These results are promising for the design of microwave devices and wireless communication equipment.
文摘Various ion sources are key components to prepare functional coatings,such as diamond-like carbon(DLC)films.In this article,we present our trying of surface modification on basis of Si-incorporation diamond-like carbon(Si-DLC)produced by a magnetic field enhanced radio frequency ion source,which is established to get high density plasma with the help of magnetic field.Under proper deposition process,a contact angle of 111°hydrophobic surface was achieved without any surface patterning,where nanostructure SiC grains appeared within the amorphous microstructure.The surface property was influenced by ion flow parameters as well as the resultant surface microstructure.The magnetic field enhanced radio frequency ion source developed in this paper was useful for protective film applications.
基金supported by the National Natural Science Foundation of China (46976019)the open project of the State Key Laboratory of Acoustics, Chinese Academy of Sciences (SKLA201202)
文摘The extraction of the weakly excited anti-symmetric Lamb wave from a submerged thin spherical shell backscattering is very difficult if the carrier frequency of the incident short tone burst is not at its frequency of greatest enhancement. Based on a single channel iterative time reversal technique, a method for isolating the subsonic anti-symmetric Lamb wave is proposed in this paper. The approach does not depend on the form function of a thin shell and any other priori knowledge, and it is also robust in the presence of some stochastic noise. Both theoretical and numerical results show that the subsonic anti-symmetric Lamb wave can be identified, even when the carrier frequency of the incident short tone burst is away from the frequency of greatest enhancement. The phenomenon may also be observed even in the case that the subsonic anti-symmetric Lamb wave is submerged in the noise, other than the case with the Signal to Noise Ratio being less than 10 d B, when the amplitude of the noise is comparable with the specular wave. In this paper, each iteration process contains a traditional transmission and time reversal transmission steps. The two steps can automatically compensate the time delay of the subsonic anti-symmetric Lamb wave relative to the specular wave and within-mode dispersion in the forward wave propagation.
基金Project supported by the Major State Basic Research Development Program of China (Grant No.2010CB328206)
文摘Based on the frequency-domain multimode theoretical model, detailed investigations on the noise characteristic of the semiconductor ring laser （SRL） are first performed in this paper. The comprehensive nonlinear terms related to the third order nonlinear susceptibility Z3 are included in this model; the Langevin noise sources for electric field and carrier density fluctuations are also taken into account. As the injection current increases, the SRL may present several operation regimes. Remarkable and unusual low frequency noise enhancement in the form of a broad low frequency tail extending all the way to the relaxation oscillation peak is observed in any of the operation regimes of SRLs. The influences of the backscattering coefficient on the relative intensity noise （RIN） spectrum in typical operation regimes are investigated in detail.
基金Project supported the Key Project of Tianjin Municipal Science and Technology Commission （Grant No 043186511）, the National Natural Science Foundation of China （Grant No 60506003）, and the Chinese-Greece International Project,
文摘Hydrogenated microcrystalline silicon （μc-Si：H） films are fabricated by very high frequency plasma enhanced chemical vapour deposition （VHF-PECVD） at a silane concentration of 7% and a varying total gas flow rate （H2＋SiH4）. Relations between the total gas flow rate and the electrical and structural properties as well as deposition rate of the films are studied. The results indicate that with the total gas flow rate increasing the photosensitivity and deposition rate increase, but the crystalline volume fraction （Xc） and dark conductivity decrease. And the intensity of （220） peak first increases then decreases with the increase of the total gas flow rate. The cause for the changes in the structure and deposition rate of the films with the total gas flow rate is investigated using optical emission spectroscopy （OES）.
文摘Due to the presence of non-stationarities and discontinuities in the audio signal, segmentation and classification of audio signal is a really challenging task. Automatic music classification and annotation is still considered as a challenging task due to the difficulty of extracting and selecting the optimal audio features. Hence, this paper proposes an efficient approach for segmentation, feature extraction and classification of audio signals. Enhanced Mel Frequency Cepstral Coefficient (EMFCC)-Enhanced Power Normalized Cepstral Coefficients (EPNCC) based feature extraction is applied for the extraction of features from the audio signal. Then, multi-level classification is done to classify the audio signal as a musical or non-musical signal. The proposed approach achieves better performance in terms of precision, Normalized Mutual Information (NMI), F-score and entropy. The PNN classifier shows high False Rejection Rate (FRR), False Acceptance Rate (FAR), Genuine Acceptance rate (GAR), sensitivity, specificity and accuracy with respect to the number of classes.
文摘This work focuses on enhancing low frequency seismic data using a convolutional neural network trained on synthetic data.Traditional seismic data often lack both high and low frequencies,which are essential for detailed geological interpretation and various geophysical applications.Low frequency data is particularly valuable for reducing wavelet sidelobes and improving full waveform inversion(FWI).Conventional methods for bandwidth extension include seismic deconvolution and sparse inversion,which have limitations in recovering low frequencies.The study explores the potential of the U-net,which has been successful in other geophysical applications such as noise attenuation and seismic resolution enhancement.The novelty in our approach is that we do not rely on computationally expensive finite difference modelling to create training data.Instead,our synthetic training data is created from individual randomly perturbed events with variations in bandwidth,making it more adaptable to different data sets compared to previous deep learning methods.The method was tested on both synthetic and real seismic data,demonstrating effective low frequency reconstruction and sidelobe reduction.With a synthetic full waveform inversion to recover a velocity model and a seismic amplitude inversion to estimate acoustic impedance we demonstrate the validity and benefit of the proposed method.Overall,the study presents a robust approach to seismic bandwidth extension using deep learning,emphasizing the importance of diverse and well-designed but computationally inexpensive synthetic training data.
