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Numerical investigation of resolution in single emitter localization-based imaging systems
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作者 Yueying WANG Yiwen HU +2 位作者 Yuehan ZHAO Cuifang KUANG Xiang HAO 《Frontiers of Information Technology & Electronic Engineering》 2025年第9期1721-1732,共12页
In this paper,we numerically analyze the factors determining localization precision and resolution in single emitter localization-based imaging systems.While previous studies have considered a limited set of parameter... In this paper,we numerically analyze the factors determining localization precision and resolution in single emitter localization-based imaging systems.While previous studies have considered a limited set of parameters,our numerical approach incorporates additional parameters with significant reference values,yielding a more comprehensive analysis of the results.We differentiate between the effects of additive and multiplicative noise on localization precision using numerical modeling and take the influence of the sampling frequency into account,computing the optimal sampling frequency for varying resolution requirements.Leveraging a suite of derived equations,we systematically simulate and quantify how variations in these parameters influence system performance.Furthermore,we provide guidelines for optimizing signal-to-noise ratio(SNR)requirements and pixel size selection based on point spread function(PSF)width in single emitter localization-based imaging systems.This numerically driven research offers critical insights for the analysis of more complex imaging systems. 展开更多
关键词 localization precision Resolution Single-point positioning Oversampling Signal-to-noise ratio(SNR)
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Local Precise Large Deviations for Independent Sums in Multi-Risk Model 被引量:2
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作者 Jinghai FENG Panpan ZHAO Libin JIAO 《Journal of Mathematical Research with Applications》 CSCD 2014年第2期240-248,共9页
In this paper, we study the case of independent sums in multi-risk model. Assume that there exist k types of variables. The ith are denoted by (Xij,j ≥ 1), which are i.i.d. with common density function fi(x) ∈ O... In this paper, we study the case of independent sums in multi-risk model. Assume that there exist k types of variables. The ith are denoted by (Xij,j ≥ 1), which are i.i.d. with common density function fi(x) ∈ OR and finite mean, i =- 1,., k. We investigate local large deviations for partial sums ∑i=1^k Sni=∑i=1^k ∑j=1^ni Xij. 展开更多
关键词 multi-risk model O-regularly varying function local precise large deviations regular density.
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Development of Precise Geoid Model for the Establishment of Consistent Height System in Geoga Grand Bridge Construction Area
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作者 Dong-Ha LEE Hong-Sic YUN 《China Ocean Engineering》 SCIE EI 2009年第4期679-694,共16页
The national benchmarks on islands were mostly established by trigonometric leveling in Korea. This method results in inaccuracy, which is a serious problem in Geoga Grand Bridge construction work that tried to link t... The national benchmarks on islands were mostly established by trigonometric leveling in Korea. This method results in inaccuracy, which is a serious problem in Geoga Grand Bridge construction work that tried to link the mainland and the islands. The Geoga Grand Bridge (Pusan-Geoje fixed link project) was selected as the study area, a huge construction work in Korea that will connect the mainland (Pnsan) and an island (Gecje island). However, the orthometric heights issued at benchmarks (JINH and GOFJ) were not consistent, because they did not refer to the same zero point, which would make the linking of the sections problematic. This paper introduces the precise local geoidas a vertical datum for the construction area in order to establish a consistent height system. To determine the precise local geoid for the construction area, we firstly developed a precise gravimetric geoid for Korea and its adjoining seas as a whole. This gravimetric geoid was developed by use of all available gravity data, including surface and satellite data on land and on the ocean. The gravimetrie gecid was computed by spherical fast fourier transform with modified Stokes' kernels. The remove-restore technique was used to eliminate the terrain effects by use of the RTM reduction and to determine the residual geoid by combining the GGM02S/EGM96 geopotential model, free-air gravity anomalies and high-resolutinn DEM data. Finally, the gravimetric model was fitted to the geoid heights obtained from GPS and tide observations (Ncps/Tiae) by least square coUocatian, to provide the final GPS-consistent local precise geoid model. The post-fit error (std. dev. ) of the final geoid to the NetS/Tide derived from GPS and tide observations was ± 2.2 cm for the construction area. We solved the height inconsistency problem by calculating the orthometric height of the benchmarks and the cnntrol points using the final geoid model. Also, the highly accurate orthometric height was estimated through the GPS/leveling technique by applying the developed local precise geoid. Therefore, the precise local geoid is expected to improve the quality of the construction procedure of the Geoga Grand Bridge. 展开更多
关键词 precise local geoid consistent height system gravity observations GPS! Tide observations least squares fitting
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MINFLUX nanoscopy enhanced with high-order vortex beams
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作者 Xiao-Jie Tan Zhiwei Huang 《Light(Science & Applications)》 2025年第7期1893-1900,共8页
Minimal photon fluxes(MINFLUX)nanoscopy has emerged as a transformative advancement in superresolution imaging,enabling unprecedented nanoscale observations across diverse biological scenarios.In this work,we propose,... Minimal photon fluxes(MINFLUX)nanoscopy has emerged as a transformative advancement in superresolution imaging,enabling unprecedented nanoscale observations across diverse biological scenarios.In this work,we propose,for the first time,that employing high-order vortex beams can significantly enhance the performance of MINFLUX,surpassing the limitations of the conventional MINFLUX using the first-order vortex beam.Our theoretical analysis indicates that,for standard MINFLUX,high-order vortex beams can improve the maximum localization precision by a factor corresponding to their order,which can approach a sub-nanometer scale under optimal conditions,and for raster scan MINFLUX,high-order vortex beams allow for a wider field of view while maintaining enhanced precision.These findings underscore the potential of high-order vortex beams to elevate the performance of MINFLUX,paving the way towards ultra-high resolution imaging for a broad range of applications. 展开更多
关键词 minimal photon fluxes minflux nanoscopy superresolution imaging localization precision NANOSCOPY high order vortex beams field view nanoscale observations minflux
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Enhanced dSTORM imaging using fluorophores interacting with cucurbituril 被引量:2
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作者 Min Zhang Jing Gao +4 位作者 Junling Chen Mingjun Cai Junguang Jiang Zhiyuan Tian Hongda Wang 《Science China Chemistry》 SCIE EI CAS CSCD 2016年第7期848-852,共5页
Advanced fluorescence microscopy including single-molecule localization-based super-resolution imaging techniques requires bright and photostable dyes orproteins asfluorophores.The photophysical properties of fluoroph... Advanced fluorescence microscopy including single-molecule localization-based super-resolution imaging techniques requires bright and photostable dyes orproteins asfluorophores.The photophysical properties of fluorophores have been proven to be crucial for super-resolution microscopy's localization precision and imaging resolution.Fluorophores TAMRA and Atto Rho6 G,which can interact with macrocyclic host cucurbit[7]uril(CB7) to form host-vip compounds,were found to improve the fluorescence intensity and lifetimes of these dyes.We enhanced the localization precision of direct stochastic optical reconstruction microscopy(dSTORM) by introducing CB7 into the imaging buffer,and showed that the number of photons as well as localizations of both TAMRA and Atto Rho6 G increase over 2 times. 展开更多
关键词 super-resolution imaging CUCURBITURIL PHOTOPHYSICAL localization precision
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Contrastive Self-Supervised Learning-Based Wireless Fingerprint Localization
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作者 Qiao Li Zhili Zhang Zhaofa Zhou 《Complex System Modeling and Simulation》 2025年第3期261-281,共21页
Recently,deeplearning based fingerprint localization has attracted significant interest due to its simplicity in implementation and effectiveness in complex multipath environments,especially for the Internet of Things... Recently,deeplearning based fingerprint localization has attracted significant interest due to its simplicity in implementation and effectiveness in complex multipath environments,especially for the Internet of Things(loT)devices in multiple-input multiple-output(MiMO)-orthogonal frequency-division multiplexing(OFDM)system.However,the huge amount of training data collection has become a challenge,which increases the labor burden of fingerprint localization heavily and hinders its large-scale implementation.In this paper,we propose a novel fingerprint localization system,termed as SiamResNet,which can be trained only on the radio map by contrastive self-supervised learning without the need for any other additional data.To be more specific,we first model the fingerprint localization problem as a dictionary look-up task.Subsequently,a channel fingerprint capturing the multipath angle and delay of wireless propagation is introduced,which exhibits excellent uniqueness,stability,and distinguishability.Meanwhile,we propose the corresponding data augmentation strategy to ensure data diversity when generating the training data from the radio map.Thus,the cost of data collection for training can be significantly reduced.Lastly,the Siamese architecture based SiamResNet is applied for location estimation,which can comprehensively extract the features of fingerprints and accurately compare the similarity of any fingerprint to the radio map in the representation space.The performance of the proposed localization method is validated through extensive simulations with a ray-tracing channel model,which demonstrates promising localization accuracy for our SiamResNet with reduced training costs. 展开更多
关键词 angle-delay channel response fingerprint high precision localization machine learning
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