In DSP-based SerDes application,it is essential for AFE to implement a pre-ADC equalization to provide a better sig-nal for ADC and DSP.To meet the various equalization requirements of different channel and transmitte...In DSP-based SerDes application,it is essential for AFE to implement a pre-ADC equalization to provide a better sig-nal for ADC and DSP.To meet the various equalization requirements of different channel and transmitter configurations,this paper presents a 112 Gbps DSP-Based PAM4 SerDes receiver with a wide band equalization tuning AFE.The AFE is realized by implementing source degeneration transconductance,feedforward high-pass branch and inductive feedback peaking TIA.The AFE offers a flexible equalization gain tuning of up to 17.5 dB at Nyquist frequency without affecting the DC gain.With the pro-posed AFE,the receiver demonstrates eye opening after digital FIR equalization and achieves 6×10^(-9) BER with a 29.6 dB inser-tion loss channel.展开更多
Early detection of Forest and Land Fires(FLF)is essential to prevent the rapid spread of fire as well as minimize environmental damage.However,accurate detection under real-world conditions,such as low light,haze,and ...Early detection of Forest and Land Fires(FLF)is essential to prevent the rapid spread of fire as well as minimize environmental damage.However,accurate detection under real-world conditions,such as low light,haze,and complex backgrounds,remains a challenge for computer vision systems.This study evaluates the impact of three image enhancement techniques—Histogram Equalization(HE),Contrast Limited Adaptive Histogram Equalization(CLAHE),and a hybrid method called DBST-LCM CLAHE—on the performance of the YOLOv11 object detection model in identifying fires and smoke.The D-Fire dataset,consisting of 21,527 annotated images captured under diverse environmental scenarios and illumination levels,was used to train and evaluate the model.Each enhancement method was applied to the dataset before training.Model performance was assessed using multiple metrics,including Precision,Recall,mean Average Precision at 50%IoU(mAP50),F1-score,and visual inspection through bounding box results.Experimental results show that all three enhancement techniques improved detection performance.HE yielded the highest mAP50 score of 0.771,along with a balanced precision of 0.784 and recall of 0.703,demonstrating strong generalization across different conditions.DBST-LCM CLAHE achieved the highest Precision score of 79%,effectively reducing false positives,particularly in scenes with dispersed smoke or complex textures.CLAHE,with slightly lower overall metrics,contributed to improved local feature detection.Each technique showed distinct advantages:HE enhanced global contrast;CLAHE improved local structure visibility;and DBST-LCM CLAHE provided an optimal balance through dynamic block sizing and local contrast preservation.These results underline the importance of selecting preprocessing methods according to detection priorities,such as minimizing false alarms or maximizing completeness.This research does not propose a new model architecture but rather benchmarks a recent lightweight detector,YOLOv11,combined with image enhancement strategies for practical deployment in FLF monitoring.The findings support the integration of preprocessing techniques to improve detection accuracy,offering a foundation for real-time FLF detection systems on edge devices or drones,particularly in regions like Indonesia.展开更多
AIM:To find the effective contrast enhancement method on retinal images for effective segmentation of retinal features.METHODS:A novel image preprocessing method that used neighbourhood-based improved contrast limited...AIM:To find the effective contrast enhancement method on retinal images for effective segmentation of retinal features.METHODS:A novel image preprocessing method that used neighbourhood-based improved contrast limited adaptive histogram equalization(NICLAHE)to improve retinal image contrast was suggested to aid in the accurate identification of retinal disorders and improve the visibility of fine retinal structures.Additionally,a minimal-order filter was applied to effectively denoise the images without compromising important retinal structures.The novel NICLAHE algorithm was inspired by the classical CLAHE algorithm,but enhanced it by selecting the clip limits and tile sized in a dynamical manner relative to the pixel values in an image as opposed to using fixed values.It was evaluated on the Drive and high-resolution fundus(HRF)datasets on conventional quality measures.RESULTS:The new proposed preprocessing technique was applied to two retinal image databases,Drive and HRF,with four quality metrics being,root mean square error(RMSE),peak signal to noise ratio(PSNR),root mean square contrast(RMSC),and overall contrast.The technique performed superiorly on both the data sets as compared to the traditional enhancement methods.In order to assess the compatibility of the method with automated diagnosis,a deep learning framework named ResNet was applied in the segmentation of retinal blood vessels.Sensitivity,specificity,precision and accuracy were used to analyse the performance.NICLAHE–enhanced images outperformed the traditional techniques on both the datasets with improved accuracy.CONCLUSION:NICLAHE provides better results than traditional methods with less error and improved contrastrelated values.These enhanced images are subsequently measured by sensitivity,specificity,precision,and accuracy,which yield a better result in both datasets.展开更多
Channel equalization plays a pivotal role within the reconstruction phase of passive radar reference signals.In the context of reconstructing digital terrestrial multimedia broadcasting(DTMB)signals for low-slow-small...Channel equalization plays a pivotal role within the reconstruction phase of passive radar reference signals.In the context of reconstructing digital terrestrial multimedia broadcasting(DTMB)signals for low-slow-small(LSS)target detection,a novel frequency domain block joint equalization algorithm is presented in this article.From the DTMB signal frame structure and channel multipath transmission characteristics,this article adopts a unconventional approach where the delay and frame structure of each DTMB signal frame are reconfigured to create a circular convolution block,facilitating concurrent fast Fourier transform(FFT)calculations.Following equalization,an inverse fast Fourier transform(IFFT)-based joint output and subsequent data reordering are executed to finalize the equalization process for the DTMB signal.Simulation and measured data confirm that this algorithm outperforms conventional techniques by reducing signal errors rate and enhancing real-time processing.In passive radar LSS detection,it effectively suppresses multipath and noise through frequency domain equalization,reducing false alarms and improving the capabilities of weak target detection.展开更多
Aiming at the traditional CUK equalizer can only perform energy equalization between adjacent batteries,if the two single batteries that need to be equalized are far away from each other,there will be the problem of l...Aiming at the traditional CUK equalizer can only perform energy equalization between adjacent batteries,if the two single batteries that need to be equalized are far away from each other,there will be the problem of longer energy transmission path and lower equalization efficiency,this paper optimizes the CUK equalizer and optimizes its peripheral selection circuit,which can support the equalization of single batteries at any two positions.The control strategy adopts the open-circuit voltage(OVC)of the battery and the state of charge(SOC)of the battery as the equalization variables,and selects the corresponding equalization variables according to the energy conditions of the two batteries that need to be equalized,and generates the adaptive equalization current with an adaptive PID controller in order to improve the equalization efficiency.Simulation modeling is performed in Matlab/Simulink 2021b,and the experimental results show that the optimized CUK equalizer in this paper improves the equalization time by 25.58%compared with the traditional CUK equalizer.In addition,compared with the mean value difference(MVD)method,the adaptive PID method reduces the equalization time by about 30%in the static and charging and discharging experimental environments,which verifies the superiority of this equalization scheme.展开更多
In this paper,an improved sag control strategy based on automatic SOC equalization is proposed to solve the problems of slow SOC equalization and excessive bus voltage fluctuation amplitude and offset caused by load a...In this paper,an improved sag control strategy based on automatic SOC equalization is proposed to solve the problems of slow SOC equalization and excessive bus voltage fluctuation amplitude and offset caused by load and PV power variations in a stand-alone DC microgrid.The strategy includes primary and secondary control.Among them,the primary control suppresses the DC microgrid voltage fluctuation through the I and II section control,and the secondary control aims to correct the P-U curve of the energy storage system and the PV system,thus reducing the steady-state bus voltage excursion.The simulation results demonstrate that the proposed control strategy effectively achieves SOC balancing and enhances the immunity of bus voltage.The proposed strategy improves the voltage fluctuation suppression ability by approximately 39.4%and 43.1%under the PV power and load power fluctuation conditions,respectively.Furthermore,the steady-state deviation of the bus voltage,△U_(dc) is only 0.01–0.1 V,ensuring stable operation of the DC microgrid in fluctuating power environments.展开更多
为解决电池在工作时出现的能量不一致的问题,以模糊逻辑控制算法为核心,建立以电池荷电状态(state of charge,SOC)差异和电池温度差为根据,可自适应选择均衡模式和开关导通占空比的均衡控制策略。并设计了一种基于环形电感和三绕组变压...为解决电池在工作时出现的能量不一致的问题,以模糊逻辑控制算法为核心,建立以电池荷电状态(state of charge,SOC)差异和电池温度差为根据,可自适应选择均衡模式和开关导通占空比的均衡控制策略。并设计了一种基于环形电感和三绕组变压器的双层均衡拓扑结构,该拓扑拥有多个均衡模式,满足策略需求。使用MATLAB Simulink软件进行模型搭建并仿真,仿真结果表明该均衡方法能够有效缩短均衡时长,缓解电池间的不一致性问题,对比同类型多均衡模式的均衡方法,静置、充电、放电所需均衡时间分别缩短69.78%、39.81%和44.15%,同时有效降低了均衡时的电池温度。展开更多
基金supported by National Key R&D Program of China No.2022YFB2803401.
文摘In DSP-based SerDes application,it is essential for AFE to implement a pre-ADC equalization to provide a better sig-nal for ADC and DSP.To meet the various equalization requirements of different channel and transmitter configurations,this paper presents a 112 Gbps DSP-Based PAM4 SerDes receiver with a wide band equalization tuning AFE.The AFE is realized by implementing source degeneration transconductance,feedforward high-pass branch and inductive feedback peaking TIA.The AFE offers a flexible equalization gain tuning of up to 17.5 dB at Nyquist frequency without affecting the DC gain.With the pro-posed AFE,the receiver demonstrates eye opening after digital FIR equalization and achieves 6×10^(-9) BER with a 29.6 dB inser-tion loss channel.
基金funded by the Directorate of Research,Technology,and Community Service,Ministry of Higher Education,Science,and Technology of the Republic of Indonesia the Regular Fundamental Research scheme,with grant numbers 001/LL6/PL/AL.04/2025,011/SPK-PFR/RIK/05/2025.
文摘Early detection of Forest and Land Fires(FLF)is essential to prevent the rapid spread of fire as well as minimize environmental damage.However,accurate detection under real-world conditions,such as low light,haze,and complex backgrounds,remains a challenge for computer vision systems.This study evaluates the impact of three image enhancement techniques—Histogram Equalization(HE),Contrast Limited Adaptive Histogram Equalization(CLAHE),and a hybrid method called DBST-LCM CLAHE—on the performance of the YOLOv11 object detection model in identifying fires and smoke.The D-Fire dataset,consisting of 21,527 annotated images captured under diverse environmental scenarios and illumination levels,was used to train and evaluate the model.Each enhancement method was applied to the dataset before training.Model performance was assessed using multiple metrics,including Precision,Recall,mean Average Precision at 50%IoU(mAP50),F1-score,and visual inspection through bounding box results.Experimental results show that all three enhancement techniques improved detection performance.HE yielded the highest mAP50 score of 0.771,along with a balanced precision of 0.784 and recall of 0.703,demonstrating strong generalization across different conditions.DBST-LCM CLAHE achieved the highest Precision score of 79%,effectively reducing false positives,particularly in scenes with dispersed smoke or complex textures.CLAHE,with slightly lower overall metrics,contributed to improved local feature detection.Each technique showed distinct advantages:HE enhanced global contrast;CLAHE improved local structure visibility;and DBST-LCM CLAHE provided an optimal balance through dynamic block sizing and local contrast preservation.These results underline the importance of selecting preprocessing methods according to detection priorities,such as minimizing false alarms or maximizing completeness.This research does not propose a new model architecture but rather benchmarks a recent lightweight detector,YOLOv11,combined with image enhancement strategies for practical deployment in FLF monitoring.The findings support the integration of preprocessing techniques to improve detection accuracy,offering a foundation for real-time FLF detection systems on edge devices or drones,particularly in regions like Indonesia.
文摘AIM:To find the effective contrast enhancement method on retinal images for effective segmentation of retinal features.METHODS:A novel image preprocessing method that used neighbourhood-based improved contrast limited adaptive histogram equalization(NICLAHE)to improve retinal image contrast was suggested to aid in the accurate identification of retinal disorders and improve the visibility of fine retinal structures.Additionally,a minimal-order filter was applied to effectively denoise the images without compromising important retinal structures.The novel NICLAHE algorithm was inspired by the classical CLAHE algorithm,but enhanced it by selecting the clip limits and tile sized in a dynamical manner relative to the pixel values in an image as opposed to using fixed values.It was evaluated on the Drive and high-resolution fundus(HRF)datasets on conventional quality measures.RESULTS:The new proposed preprocessing technique was applied to two retinal image databases,Drive and HRF,with four quality metrics being,root mean square error(RMSE),peak signal to noise ratio(PSNR),root mean square contrast(RMSC),and overall contrast.The technique performed superiorly on both the data sets as compared to the traditional enhancement methods.In order to assess the compatibility of the method with automated diagnosis,a deep learning framework named ResNet was applied in the segmentation of retinal blood vessels.Sensitivity,specificity,precision and accuracy were used to analyse the performance.NICLAHE–enhanced images outperformed the traditional techniques on both the datasets with improved accuracy.CONCLUSION:NICLAHE provides better results than traditional methods with less error and improved contrastrelated values.These enhanced images are subsequently measured by sensitivity,specificity,precision,and accuracy,which yield a better result in both datasets.
文摘Channel equalization plays a pivotal role within the reconstruction phase of passive radar reference signals.In the context of reconstructing digital terrestrial multimedia broadcasting(DTMB)signals for low-slow-small(LSS)target detection,a novel frequency domain block joint equalization algorithm is presented in this article.From the DTMB signal frame structure and channel multipath transmission characteristics,this article adopts a unconventional approach where the delay and frame structure of each DTMB signal frame are reconfigured to create a circular convolution block,facilitating concurrent fast Fourier transform(FFT)calculations.Following equalization,an inverse fast Fourier transform(IFFT)-based joint output and subsequent data reordering are executed to finalize the equalization process for the DTMB signal.Simulation and measured data confirm that this algorithm outperforms conventional techniques by reducing signal errors rate and enhancing real-time processing.In passive radar LSS detection,it effectively suppresses multipath and noise through frequency domain equalization,reducing false alarms and improving the capabilities of weak target detection.
基金Natural Science Foundation of China(51677058)Scientific Research Program of Hubei Provincial Department of Education(T2021005).
文摘Aiming at the traditional CUK equalizer can only perform energy equalization between adjacent batteries,if the two single batteries that need to be equalized are far away from each other,there will be the problem of longer energy transmission path and lower equalization efficiency,this paper optimizes the CUK equalizer and optimizes its peripheral selection circuit,which can support the equalization of single batteries at any two positions.The control strategy adopts the open-circuit voltage(OVC)of the battery and the state of charge(SOC)of the battery as the equalization variables,and selects the corresponding equalization variables according to the energy conditions of the two batteries that need to be equalized,and generates the adaptive equalization current with an adaptive PID controller in order to improve the equalization efficiency.Simulation modeling is performed in Matlab/Simulink 2021b,and the experimental results show that the optimized CUK equalizer in this paper improves the equalization time by 25.58%compared with the traditional CUK equalizer.In addition,compared with the mean value difference(MVD)method,the adaptive PID method reduces the equalization time by about 30%in the static and charging and discharging experimental environments,which verifies the superiority of this equalization scheme.
基金supported by the NationalNatural Science Foundation of China(No.52067013)the Natural Science Foundation of Gansu Province(No.20JR5RA395)as well as the Tianyou Innovation Team of Lanzhou Jiaotong University(TY202010).
文摘In this paper,an improved sag control strategy based on automatic SOC equalization is proposed to solve the problems of slow SOC equalization and excessive bus voltage fluctuation amplitude and offset caused by load and PV power variations in a stand-alone DC microgrid.The strategy includes primary and secondary control.Among them,the primary control suppresses the DC microgrid voltage fluctuation through the I and II section control,and the secondary control aims to correct the P-U curve of the energy storage system and the PV system,thus reducing the steady-state bus voltage excursion.The simulation results demonstrate that the proposed control strategy effectively achieves SOC balancing and enhances the immunity of bus voltage.The proposed strategy improves the voltage fluctuation suppression ability by approximately 39.4%and 43.1%under the PV power and load power fluctuation conditions,respectively.Furthermore,the steady-state deviation of the bus voltage,△U_(dc) is only 0.01–0.1 V,ensuring stable operation of the DC microgrid in fluctuating power environments.
文摘为解决电池在工作时出现的能量不一致的问题,以模糊逻辑控制算法为核心,建立以电池荷电状态(state of charge,SOC)差异和电池温度差为根据,可自适应选择均衡模式和开关导通占空比的均衡控制策略。并设计了一种基于环形电感和三绕组变压器的双层均衡拓扑结构,该拓扑拥有多个均衡模式,满足策略需求。使用MATLAB Simulink软件进行模型搭建并仿真,仿真结果表明该均衡方法能够有效缩短均衡时长,缓解电池间的不一致性问题,对比同类型多均衡模式的均衡方法,静置、充电、放电所需均衡时间分别缩短69.78%、39.81%和44.15%,同时有效降低了均衡时的电池温度。
