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
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
Four-level pulse amplitude modulation(PAM4)signals,recognized for enhanced energy efficiency and spectral utilization compared with non-return-to-zero(NRZ)counterparts,have been adopted in multiple high-speed serializ...Four-level pulse amplitude modulation(PAM4)signals,recognized for enhanced energy efficiency and spectral utilization compared with non-return-to-zero(NRZ)counterparts,have been adopted in multiple high-speed serializer/deserializer(SerDes)standards,but NRZ modulation remains predominant in industrial applications.This paper introduces a UMC 28 nm CMOS-based parallel configurable forward feedback equalization(FFE)dual-mode high-speed SerDes transmitter supporting 7-bit resolution with data rates of 56 Gb∙s^(-1)NRZ and 112 Gb∙s^(-1)PAM4,utilizing a hybrid architecture that integrates digital signal processing(DSP)with digital-to-analog conversion(DAC).The design processes parallel input signals and eight stored 8-bit tap coefficients through a configurable FFE multiplier module and parallel carry adder module,while achieving low-power serialization via low-speed 16∶4 multiplexers(MUXs)with two different 2∶1 MUXs and high-speed 4∶1 MUXs.A source series termination(SST)output network structure enhances lower power dissipation and higher output swing.Simulation results show that,under a 1.05 V supply voltage and a channel loss of 19.21 dB at 28 GHz,the output 56 Gb∙s^(-1)NRZ eye diagram has an eye height of 70.11 mV and an eye width of 12.16 ps(0.68 UI).The output 112 Gb∙s^(-1)PAM4 eye diagram has an eye height of 20.07 mV and an eye width of 7.49 ps(0.42 UI).The layout area of the dual-mode transmitter is 0.079 mm^(2),and the total circuit power consumption is 74.48 mW(energy efficiency is 1.33/0.67 pJ∙bit-1).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
Eigenstructure-based coherence attributes are efficient and mature techniques for large-scale fracture detection. However, in horizontally bedded and continuous strata, buried fractures in high grayscale value zones a...Eigenstructure-based coherence attributes are efficient and mature techniques for large-scale fracture detection. However, in horizontally bedded and continuous strata, buried fractures in high grayscale value zones are difficult to detect. Furthermore, middleand small-scale fractures in fractured zones where migration image energies are usually not concentrated perfectly are also hard to detect because of the fuzzy, clouded shadows owing to low grayscale values. A new fracture enhancement method combined with histogram equalization is proposed to solve these problems. With this method, the contrast between discontinuities and background in coherence images is increased, linear structures are highlighted by stepwise adjustment of the threshold of the coherence image, and fractures are detected at different scales. Application of the method shows that it can also improve fracture cognition and accuracy.展开更多
A new approach for blind equalization and channel identification is proposed in this paper. The equalization scheme is based on over sampling technique and an independent component analysis network. The equalized seq...A new approach for blind equalization and channel identification is proposed in this paper. The equalization scheme is based on over sampling technique and an independent component analysis network. The equalized sequence and its higher order statistics are used to identify the channel parameters. Compared to traditional equalization methods, the proposed approach is with a simple architecture, and does not need learning sequences. Computer simulations show the validity of the proposed method.展开更多
To decrease the complexity of MAP algorithm, reduced state or reduced search techniques can be applied. In this paper we propose a reduced search soft output detection algorithm fully based on the principle of M a...To decrease the complexity of MAP algorithm, reduced state or reduced search techniques can be applied. In this paper we propose a reduced search soft output detection algorithm fully based on the principle of M algorithm for turbo equalization, which is a suboptimum version of the Lee algorithm. This algorithm is called soft output M algorithm (denoted as SO M algorithm), which applies the M strategy to both the forward recursion and the extended forward recursion of the Lee algorithm. Computer simulation results show that, by properly selecting and adjusting the breadth parameter and depth parameter during the iteration of turbo equalization, this algorithm can obtain good performance and complexity trade off.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.
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.
基金Supported by the National Key R&D Program Broadband Communications and New Network Key Special Project(No.2019YFB1803600).
文摘Four-level pulse amplitude modulation(PAM4)signals,recognized for enhanced energy efficiency and spectral utilization compared with non-return-to-zero(NRZ)counterparts,have been adopted in multiple high-speed serializer/deserializer(SerDes)standards,but NRZ modulation remains predominant in industrial applications.This paper introduces a UMC 28 nm CMOS-based parallel configurable forward feedback equalization(FFE)dual-mode high-speed SerDes transmitter supporting 7-bit resolution with data rates of 56 Gb∙s^(-1)NRZ and 112 Gb∙s^(-1)PAM4,utilizing a hybrid architecture that integrates digital signal processing(DSP)with digital-to-analog conversion(DAC).The design processes parallel input signals and eight stored 8-bit tap coefficients through a configurable FFE multiplier module and parallel carry adder module,while achieving low-power serialization via low-speed 16∶4 multiplexers(MUXs)with two different 2∶1 MUXs and high-speed 4∶1 MUXs.A source series termination(SST)output network structure enhances lower power dissipation and higher output swing.Simulation results show that,under a 1.05 V supply voltage and a channel loss of 19.21 dB at 28 GHz,the output 56 Gb∙s^(-1)NRZ eye diagram has an eye height of 70.11 mV and an eye width of 12.16 ps(0.68 UI).The output 112 Gb∙s^(-1)PAM4 eye diagram has an eye height of 20.07 mV and an eye width of 7.49 ps(0.42 UI).The layout area of the dual-mode transmitter is 0.079 mm^(2),and the total circuit power consumption is 74.48 mW(energy efficiency is 1.33/0.67 pJ∙bit-1).
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.
基金sponsored by the National Science&Technology Major Special Project(Grant No.2011ZX05025-001-04)
文摘Eigenstructure-based coherence attributes are efficient and mature techniques for large-scale fracture detection. However, in horizontally bedded and continuous strata, buried fractures in high grayscale value zones are difficult to detect. Furthermore, middleand small-scale fractures in fractured zones where migration image energies are usually not concentrated perfectly are also hard to detect because of the fuzzy, clouded shadows owing to low grayscale values. A new fracture enhancement method combined with histogram equalization is proposed to solve these problems. With this method, the contrast between discontinuities and background in coherence images is increased, linear structures are highlighted by stepwise adjustment of the threshold of the coherence image, and fractures are detected at different scales. Application of the method shows that it can also improve fracture cognition and accuracy.
文摘A new approach for blind equalization and channel identification is proposed in this paper. The equalization scheme is based on over sampling technique and an independent component analysis network. The equalized sequence and its higher order statistics are used to identify the channel parameters. Compared to traditional equalization methods, the proposed approach is with a simple architecture, and does not need learning sequences. Computer simulations show the validity of the proposed method.
文摘To decrease the complexity of MAP algorithm, reduced state or reduced search techniques can be applied. In this paper we propose a reduced search soft output detection algorithm fully based on the principle of M algorithm for turbo equalization, which is a suboptimum version of the Lee algorithm. This algorithm is called soft output M algorithm (denoted as SO M algorithm), which applies the M strategy to both the forward recursion and the extended forward recursion of the Lee algorithm. Computer simulation results show that, by properly selecting and adjusting the breadth parameter and depth parameter during the iteration of turbo equalization, this algorithm can obtain good performance and complexity trade off.
