To effectively extract multi-scale information from observation data and improve computational efficiency,a multi-scale second-order autoregressive recursive filter(MSRF)method is designed.The second-order autoregress...To effectively extract multi-scale information from observation data and improve computational efficiency,a multi-scale second-order autoregressive recursive filter(MSRF)method is designed.The second-order autoregressive filter used in this study has been attempted to replace the traditional first-order recursive filter used in spatial multi-scale recursive filter(SMRF)method.The experimental results indicate that the MSRF scheme successfully extracts various scale information resolved by observations.Moreover,compared with the SMRF scheme,the MSRF scheme improves computational accuracy and efficiency to some extent.The MSRF scheme can not only propagate to a longer distance without the attenuation of innovation,but also reduce the mean absolute deviation between the reconstructed sea ice concentration results and observations reduced by about 3.2%compared to the SMRF scheme.On the other hand,compared with traditional first-order recursive filters using in the SMRF scheme that multiple filters are executed,the MSRF scheme only needs to perform two filter processes in one iteration,greatly improving filtering efficiency.In the two-dimensional experiment of sea ice concentration,the calculation time of the MSRF scheme is only 1/7 of that of SMRF scheme.This means that the MSRF scheme can achieve better performance with less computational cost,which is of great significance for further application in real-time ocean or sea ice data assimilation systems in the future.展开更多
Heartbeat detection stays central to cardiovascular an electrocardiogram(ECG)is used to help with disease diagnosis and management.Existing Convolutional Neural Network(CNN)-based methods suffer from the less generali...Heartbeat detection stays central to cardiovascular an electrocardiogram(ECG)is used to help with disease diagnosis and management.Existing Convolutional Neural Network(CNN)-based methods suffer from the less generalization problem thus;the effectiveness and robustness of the traditional heartbeat detector methods cannot be guaranteed.In contrast,this work proposes a heartbeat detector Krill based Deep Neural Network Stacked Auto Encoders(KDNN-SAE)that computes the disease before the exact heart rate by combining features from multiple ECG Signals.Heartbeats are classified independently and multiple signals are fused to estimate life threatening conditions earlier without any error in classification of heart beat.This work contained Training and testing stages,in the preparation part at first the Adaptive Filter Enthalpy-based Empirical Mode Decomposition(EMD)is utilized to eliminate the motion artifact in the signal.At that point,the robotic process automation(RPA)learning part extracts the effective features are extracted,and normalized the value of the feature then estimated utilizing the RPA loss function.At last KDNN-SAE prepared training for the data stored in the dataset.In the subsequent stage,input signal compute motion artifact and RPA Learning the evaluation part determines the detection of Heartbeat.So early diagnosis of heart failures is an essential factor.The results of the experiments show that our proposed method has a high score outcome of 0.9997.Comparable to the CIF,which reaches 0.9990.The CNN and Artificial Neural Network(ANN)had less score 0.95115 and 0.90147.展开更多
Auto anti-collision technology is one of the main research subjects of automobiles’ safety technology. Aiming at the key technology of Auto anti-collision, measuring the distance from obstacles, based on the theory o...Auto anti-collision technology is one of the main research subjects of automobiles’ safety technology. Aiming at the key technology of Auto anti-collision, measuring the distance from obstacles, based on the theory of phase laser distance ranging, Laser Diode (LD) distance-measuring system for auto anti-collision has been developed to solve the problem of on-line measuring distance technology in middle to long distance utilizing the good characteristics of LD when modulating its optical intensity and adopting typical kinds of filter techniques in this paper. By theoretical analysis, adopting typical kinds of filter techniques can reduce the interference of strong light, so distance-measuring range can be 0.5–100 m in daytime or 1–200 m at night. And more, from theoretical analysis and experiment result, it can guarantee the high measuring resolution which can be less than 24.5 mm, utilizing the method of two Laser Diode optical intensity modulating wavelength and complimenting precise calibration and revision. The idea of LD distance-measuring technology is novel and feasible and this technology can be applied in Auto anti-collision. Key words laser diode - phase laser distance ranging - filter techniques - auto anti-collision CLC number TH 161 Foundation item: Supported by the National Natural Science Foundation of China (59675080, 59805006) and Wuhan Chenguang Foundation (20025001001)Biography: Zhang Xin-bao (1965-), male, Associate professor, research direction: precise mechanism and instrument.展开更多
An active-RC low-pass filter of 5MHz cutoff frequency with a tuning architecture is proposed. It is implemented in 0. 18μm standard CMOS technology. The accuracy of the tuning system is improved to be within （ - 1.2...An active-RC low-pass filter of 5MHz cutoff frequency with a tuning architecture is proposed. It is implemented in 0. 18μm standard CMOS technology. The accuracy of the tuning system is improved to be within （ - 1.24%, ＋ 2.16%） in measurement. The chip area of the tuning system is only a quarter of that of the main-filter. After tuning is completed, the tuning system will be turned off automatically to save power and to avoid interference. The in-band 3rd order harmonic input intercept point （IIP3） is larger than 16. ldBm, with 50Ω as the source impedance. The input referred noise is about 36μVrms The measured group delay variation of the filter between 3 and 5MHz is only 24ns,and the filter power consump- tion is 3.6roW. This filter with the tuning system is realized easily and can be used in many wireless low-IF receiver applications, such as global position systems （GPS）, global system for mobile communications （GSM） and code division multiple access （CDMA） chips.展开更多
基金The National Key Research and Development Program of China under contract No.2023YFC3107701the National Natural Science Foundation of China under contract No.42375143.
文摘To effectively extract multi-scale information from observation data and improve computational efficiency,a multi-scale second-order autoregressive recursive filter(MSRF)method is designed.The second-order autoregressive filter used in this study has been attempted to replace the traditional first-order recursive filter used in spatial multi-scale recursive filter(SMRF)method.The experimental results indicate that the MSRF scheme successfully extracts various scale information resolved by observations.Moreover,compared with the SMRF scheme,the MSRF scheme improves computational accuracy and efficiency to some extent.The MSRF scheme can not only propagate to a longer distance without the attenuation of innovation,but also reduce the mean absolute deviation between the reconstructed sea ice concentration results and observations reduced by about 3.2%compared to the SMRF scheme.On the other hand,compared with traditional first-order recursive filters using in the SMRF scheme that multiple filters are executed,the MSRF scheme only needs to perform two filter processes in one iteration,greatly improving filtering efficiency.In the two-dimensional experiment of sea ice concentration,the calculation time of the MSRF scheme is only 1/7 of that of SMRF scheme.This means that the MSRF scheme can achieve better performance with less computational cost,which is of great significance for further application in real-time ocean or sea ice data assimilation systems in the future.
文摘Heartbeat detection stays central to cardiovascular an electrocardiogram(ECG)is used to help with disease diagnosis and management.Existing Convolutional Neural Network(CNN)-based methods suffer from the less generalization problem thus;the effectiveness and robustness of the traditional heartbeat detector methods cannot be guaranteed.In contrast,this work proposes a heartbeat detector Krill based Deep Neural Network Stacked Auto Encoders(KDNN-SAE)that computes the disease before the exact heart rate by combining features from multiple ECG Signals.Heartbeats are classified independently and multiple signals are fused to estimate life threatening conditions earlier without any error in classification of heart beat.This work contained Training and testing stages,in the preparation part at first the Adaptive Filter Enthalpy-based Empirical Mode Decomposition(EMD)is utilized to eliminate the motion artifact in the signal.At that point,the robotic process automation(RPA)learning part extracts the effective features are extracted,and normalized the value of the feature then estimated utilizing the RPA loss function.At last KDNN-SAE prepared training for the data stored in the dataset.In the subsequent stage,input signal compute motion artifact and RPA Learning the evaluation part determines the detection of Heartbeat.So early diagnosis of heart failures is an essential factor.The results of the experiments show that our proposed method has a high score outcome of 0.9997.Comparable to the CIF,which reaches 0.9990.The CNN and Artificial Neural Network(ANN)had less score 0.95115 and 0.90147.
文摘Auto anti-collision technology is one of the main research subjects of automobiles’ safety technology. Aiming at the key technology of Auto anti-collision, measuring the distance from obstacles, based on the theory of phase laser distance ranging, Laser Diode (LD) distance-measuring system for auto anti-collision has been developed to solve the problem of on-line measuring distance technology in middle to long distance utilizing the good characteristics of LD when modulating its optical intensity and adopting typical kinds of filter techniques in this paper. By theoretical analysis, adopting typical kinds of filter techniques can reduce the interference of strong light, so distance-measuring range can be 0.5–100 m in daytime or 1–200 m at night. And more, from theoretical analysis and experiment result, it can guarantee the high measuring resolution which can be less than 24.5 mm, utilizing the method of two Laser Diode optical intensity modulating wavelength and complimenting precise calibration and revision. The idea of LD distance-measuring technology is novel and feasible and this technology can be applied in Auto anti-collision. Key words laser diode - phase laser distance ranging - filter techniques - auto anti-collision CLC number TH 161 Foundation item: Supported by the National Natural Science Foundation of China (59675080, 59805006) and Wuhan Chenguang Foundation (20025001001)Biography: Zhang Xin-bao (1965-), male, Associate professor, research direction: precise mechanism and instrument.
文摘An active-RC low-pass filter of 5MHz cutoff frequency with a tuning architecture is proposed. It is implemented in 0. 18μm standard CMOS technology. The accuracy of the tuning system is improved to be within （ - 1.24%, ＋ 2.16%） in measurement. The chip area of the tuning system is only a quarter of that of the main-filter. After tuning is completed, the tuning system will be turned off automatically to save power and to avoid interference. The in-band 3rd order harmonic input intercept point （IIP3） is larger than 16. ldBm, with 50Ω as the source impedance. The input referred noise is about 36μVrms The measured group delay variation of the filter between 3 and 5MHz is only 24ns,and the filter power consump- tion is 3.6roW. This filter with the tuning system is realized easily and can be used in many wireless low-IF receiver applications, such as global position systems （GPS）, global system for mobile communications （GSM） and code division multiple access （CDMA） chips.
