We demonstrate a new polarization smoothing(PS)approach utilizing residual stress birefringence in fused silica to create a spatially random polarization control plate(SRPCP),thereby improving target illumination unif...We demonstrate a new polarization smoothing(PS)approach utilizing residual stress birefringence in fused silica to create a spatially random polarization control plate(SRPCP),thereby improving target illumination uniformity in inertial confinement fusion(ICF)laser systems.The fundamental operating mechanism and key fabrication techniques for the SRPCP are systematically developed and experimentally validated.The SRPCP converts a linearly polarized 3ω incident laser beam into an output beam with a spatially randomized polarization distribution.When combined with a continuous phase plate,the SRPCP effectively suppresses high-intensity speckles at all spatial frequencies in the focal spot.The proposed PS technique is specifically designed for high-fluence large-aperture laser systems,enabling novel polarization control regimes in laser-driven ICF.展开更多
Based on Evans’spatial smoothing preprocessing scheme,a new approach calledtwo-direction spatial smoothing preprocessing method is presented.It is proved that the decorre-lation,the effective aperture and the maximum...Based on Evans’spatial smoothing preprocessing scheme,a new approach calledtwo-direction spatial smoothing preprocessing method is presented.It is proved that the decorre-lation,the effective aperture and the maximum number of distinguishable coherent signals(whenarray size is given)of the new method are better than those of the Evans’method.Simulationresults give a comparison between the eigenvector spectrums produced by the two methods.展开更多
A full-polarimetric super-resolution algorithm with spatial smoothing processing is presented for one-dimensional（1-D）radar imaging.The coherence between scattering centers is minimized by using spatial smoothing pr...A full-polarimetric super-resolution algorithm with spatial smoothing processing is presented for one-dimensional（1-D）radar imaging.The coherence between scattering centers is minimized by using spatial smoothing processing（SSP）.Then the range and polarimetric scattering matrix of the scattering centers are estimated.The impact of different lengths of the smoothing window on the imaging quality is mainly analyzed with different signal-to-noise ratios（SNR）.Simulation and experimental results show that an improved radar super-resolution range profile and more precise estimation can be obtained by adjusting the length of the smoothing window under different SNR conditions.展开更多
A novel method to estimate DOA of coherent signals impinging on a uniform circular array( UCA) is presented in this paper. A virtual uniform linear array (VULA) is first derived by using spatial DFT technique, transfo...A novel method to estimate DOA of coherent signals impinging on a uniform circular array( UCA) is presented in this paper. A virtual uniform linear array (VULA) is first derived by using spatial DFT technique, transforming the UCA from element space to phase mode space to obtain the properties of ordinary ULA, and then the well known spatial smoothing technique is applied to the VULA so that the lost rank of covariance matrix due to signal coherence can be retrieved. This method makes it feasible to use the simple MUSIC algorithm to estimate DOA of coherent signals impinging on a UCA without heavy computation burden. Simulation results strongly verify the effectiveness of the algorithm.展开更多
The performance the quaternion-Capon（ Q-Capon） beamformer degraded when suppressing the interferences that are coherent with the signal of interest（ SOI）. To tackle the problem,the spatial smoothing technique is a...The performance the quaternion-Capon（ Q-Capon） beamformer degraded when suppressing the interferences that are coherent with the signal of interest（ SOI）. To tackle the problem,the spatial smoothing technique is adopted in quaternion domain to decorrelate the interferences by using linearly and uniformly spaced two-component electromagnetic vector-sensors. By averaging several translational invariant subarray quaternion covariance matrices,the quaternion spatial smoothing is performed to prevent the SOI cancellation phenomena caused by the presence of coherent interferences. It is demonstrated that the quaternion spatial smoothing Q-Capon beamformer can suppress the coherent interferences remarkably while the computational cost is lower than the complex domain long vector spatial smoothing counterpart. Theoretical analyses and simulation results validate the efficacy of the spatially smoothed Q-Capon beamformer in terms of coherent interference suppression capability.展开更多
In this study, the North China seismic region was selected as the study area, and evaluation of seismic hazard using the spatial smoothing seismicity model was performed. Firstly, the study area is divided into grids,...In this study, the North China seismic region was selected as the study area, and evaluation of seismic hazard using the spatial smoothing seismicity model was performed. Firstly, the study area is divided into grids, and some parameters （e. g. b-value, Mo, Me, azimuth and M-L relationship ） for each seismotectonic model were assigned. Secondly, using elliptical smoothing based on a seismotectonic background model, the statistical earthquake incidence rate in each grid is successively calculated. Lastly, the relevant ground motion attenuation relationship is chosen to assess seismic hazard of general sites. The maps for the distribution of horizontal peak ground acceleration with 10% probability of exceedance in 50 years were obtained by using the seismic hazard analysis method based on grid source. This seismicity model simplifies the methodology of probabilistic seismic hazard analysis, especially appropriate for those places where seismic tectonics is not yet clearly known. This method can provide valuable references for seismic zonation and seismic safety assessment for significant engineering projects.展开更多
The northern segment of the North-South Seismic Belt is characterized by intense crustal deformation,well-developed active tectonics,and frequent occurrences of strong earthquakes.Therefore,conducting a Probabilistic ...The northern segment of the North-South Seismic Belt is characterized by intense crustal deformation,well-developed active tectonics,and frequent occurrences of strong earthquakes.Therefore,conducting a Probabilistic Seismic Hazard Analysis(PSHA)for this region is of significant importance for supporting seismic fortification in major engineering projects and formulating disaster prevention and mitigation policies.In this study,a composite seismic source model was constructed by integrating data on historical earthquakes,active faults,and paleoseismicity.Furthermore,a logic tree framework was employed to quantify epistemic uncertainties,enabling a systematic seismic hazard assessment of the region.To more accurately characterize the spatial heterogeneity of seismic activity,improvements were made to both the Circular Spatial Smoothing Model(CSSM)with a fixed radius and the Adaptive Spatial Smoothing Model(ASSM),with full consideration given to the spatiotemporal completeness of historical earthquake magnitudes.Regarding the CSSM,for scenarios involving small sample sizes in earthquake catalogs,the cross-validation method proposed in this study demonstrated higher robustness than the maximum likelihood method in determining the optimal correlation distance.Performance evaluation results indicate that while both models effectively characterize seismic activity,the ASSM exhibits superior overall predictive performance compared to the CSSM,owing to its ability to adaptively adjust the smoothing radius according to seismic density.Significant discrepancies were observed in the Peak Ground Acceleration(PGA)results calculated with a 10%probability of exceedance in 50 years across different combinations of seismic source models.The single spatially smoothed point-source model yielded a maximum PGA of approximately 0.52 g,with high-value areas concentrated near historical epicenters,thereby significantly underestimating the hazard associated with major fault zones.When combined with the simple fault-source model,the maximum PGA increased to 0.8 g,with high-value zones exhibiting a zonal distribution along faults;however,the risk remained underestimated for faults with low slip rates that are nevertheless approaching their recurrence cycles.Following the introduction of the time-dependent characteristic fault-source model,local PGA values for faults in the middle-to-late stages of their recurrence cycles increased by a factor of 2 to 7 compared to the single model.These results demonstrate that the characteristic fault-source model reasonably delineates the time-dependence of large earthquake recurrence,thereby providing a more accurate assessment of imminent seismic risks.By comprehensively applying the improved spatially smoothed pointsource model,the simple fault-source model,and the characteristic fault-source model,the following faults within the region were identified as having high seismic hazard:the Huangxianggou,Zhangxian,and Tianshui segments of the Xiqinling northern edge fault;the Maqin-Maqu segment of the Dongkunlun fault;the Longriqu fault;the Maoergai fault;the Elashan fault;the Riyueshan fault;the eastern segment of the Lenglongling fault;the Maxianshan segment of the Maxianshan northern Margin fault;and the Maomaoshan-Jinqianghe segment of the Laohushan-Maomaoshan fault.As these faults are located within seismic gaps or are approaching the recurrence periods of large earthquakes,they should be prioritized for current and future seismic monitoring as well as disaster prevention and mitigation efforts.展开更多
在相干信号波达方向(direction of arrival,DOA)估计中,当阵列接收到的相干信号处于低信噪比时,DOA估计性能会大大降低。针对该问题,提出一种增强的时空平滑(enhanced spatio-temporal smoothing,ESTS)算法,在使用时空相关矩阵重构接收...在相干信号波达方向(direction of arrival,DOA)估计中,当阵列接收到的相干信号处于低信噪比时,DOA估计性能会大大降低。针对该问题,提出一种增强的时空平滑(enhanced spatio-temporal smoothing,ESTS)算法,在使用时空相关矩阵重构接收数据矩阵的时空平滑(spatio-temporal smoothing,STS)方法的基础上进行了改进。首先对子阵列时空相关矩阵进行平方预处理,然后通过充分利用子阵列时空相关矩阵的协方差和互协方差信息解相干,提高了相干信号的分辨率以及对噪声扰动的鲁棒性。理论分析和统计结果均表明,与其他空间平滑类解相干方法相比,该方法提高了在低信噪比、少快拍数、小角度分离情况下的相干信号DOA估计的去相关性能。展开更多
This study proposed a random Smoothed Particle Hydrodynamics method for analyzing the post-failure behavior of landslides,which is based on the Karhunen-Loeve(K-L) expansion,the non-Newtonian fluid model,and the OpenM...This study proposed a random Smoothed Particle Hydrodynamics method for analyzing the post-failure behavior of landslides,which is based on the Karhunen-Loeve(K-L) expansion,the non-Newtonian fluid model,and the OpenMP parallel framework.Then,the applicability of this method was validated by comparing the generated random field with theoretical result and by simulating the post-failure process of an actual landslide.Thereafter,an illustrative landslide example was created and simulated to obtain the spatial variability effect of internal friction angle on the post-failure behavior of landslides under different coefficients of variation(COVs) and correlation lengths(CLs).As a conclusion,the reinforcement with materials of a larger friction angle can reduce the runout distance and impact the force of a landslide.As the increase of COV,the distribution range of influence zones also increases,which indicates that the deviation of influence zones becomes large.In addition,the correlation length in Monte Carlo simulations should not be too small,otherwise the variation range of influence zones will be underestimated.展开更多
A novel correlation-based filter is presented for de-noising functional magnetic resonance imaging (fMRI) data.Temporal correlation-based exponential weights are defined for spatial smoothing of the data,with bias red...A novel correlation-based filter is presented for de-noising functional magnetic resonance imaging (fMRI) data.Temporal correlation-based exponential weights are defined for spatial smoothing of the data,with bias reduction using estimated noise variance.The proposed scheme is tested on simulated and real fMRI data.Finally,the results are compared with conventional filters.The method is found to be effectively suppressing the Rician noise in fMRI data,while improving the SNR.展开更多
Spatial modeling has largely been applied in epidemiology and disease modeling. Different methods such as Generalized linear models (GLMs) have been made available to prediction of the claim frequencies. However, due ...Spatial modeling has largely been applied in epidemiology and disease modeling. Different methods such as Generalized linear models (GLMs) have been made available to prediction of the claim frequencies. However, due to heterogeneity nature of policies, the methods do not generate precise and accurate claim frequencies predictions;these parametric statistical methods extensively depend on limiting assumptions (linearity, normality, independence among predictor variables, and a pre-existing functional form relating the criterion variable and predictive variables). This study investigates how to derive a spatial nonparametric model estimator based on smoothing Spline for predicting claim frequencies. The simulation results showed that the proposed estimator is efficient for prediction of claim frequencies than the kernel based counterpart. The estimator derived was applied to a sample of 6500 observations obtained from Cooperative Insurance Company, Kenya for the period of 2018-2020 and the results showed that the proposed method perform<span style="font-family:Verdana;">s</span><span style="font-family:Verdana;"> better than the kernel based counterpart. It is worth noting that inclusion of the spatial effects significantly improves the estimator prediction of claim frequency.</span>展开更多
叶端定时是航空发动机叶片叶端振动非接触测量的有效手段,但其采样模式决定了所采信号具有高度欠采样特征,需要进行抗混叠频谱分析从而提取转子叶片固有频率这一关键指标。利用了前向平滑策略的改进多重信号分类法(multiple sIgnal clas...叶端定时是航空发动机叶片叶端振动非接触测量的有效手段,但其采样模式决定了所采信号具有高度欠采样特征,需要进行抗混叠频谱分析从而提取转子叶片固有频率这一关键指标。利用了前向平滑策略的改进多重信号分类法(multiple sIgnal classification,MUSIC)能实现抗混叠但无法充分发挥平滑方法的优势。因此,提出适用于叶端定时信号处理的前后向平滑MUSIC法,通过建立传感器的对称布局条件,利用前后向平滑方法代替前向平滑方法,得到更准确的自相关矩阵估计,进而提高叶片固有频率估计性能,并通过仿真和试验验证了在样本数量、算法参数等相同的情况下,前后向平滑MUSIC法的混叠与噪声抑制能力得到了提升。展开更多
Abstract A brain network consisting of two key parietal nodes, the precuneus and the posterior cingulate cortex, has emerged from recent fMRI studies. Though it is anatomically adjacent to and spatially overlaps with ...Abstract A brain network consisting of two key parietal nodes, the precuneus and the posterior cingulate cortex, has emerged from recent fMRI studies. Though it is anatomically adjacent to and spatially overlaps with the default mode network （DMN）, its function has been associated with memory processing, and it has been referred to as the parietal memory network （PMN）. Independent component analysis （ICA） is the most common data-driven method used to extract PMN and DMN simultaneously. However, the effects of data preprocessing and parameter determi- nation in ICA on PMN-DMN segregation are completely unknown. Here, we employ three typical algorithms of group ICA to assess how spatial smoothing and model order influence the degree of PMN-DMN segregation. Our findings indicate that PMN and DMN can only be stably separated using a combination of low-level spatial smoothing and high model order across the three ICA algorithms. We thus argue for more considerations on parametric settings for interpreting DMN data.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.62275235).
文摘We demonstrate a new polarization smoothing(PS)approach utilizing residual stress birefringence in fused silica to create a spatially random polarization control plate(SRPCP),thereby improving target illumination uniformity in inertial confinement fusion(ICF)laser systems.The fundamental operating mechanism and key fabrication techniques for the SRPCP are systematically developed and experimentally validated.The SRPCP converts a linearly polarized 3ω incident laser beam into an output beam with a spatially randomized polarization distribution.When combined with a continuous phase plate,the SRPCP effectively suppresses high-intensity speckles at all spatial frequencies in the focal spot.The proposed PS technique is specifically designed for high-fluence large-aperture laser systems,enabling novel polarization control regimes in laser-driven ICF.
文摘Based on Evans’spatial smoothing preprocessing scheme,a new approach calledtwo-direction spatial smoothing preprocessing method is presented.It is proved that the decorre-lation,the effective aperture and the maximum number of distinguishable coherent signals(whenarray size is given)of the new method are better than those of the Evans’method.Simulationresults give a comparison between the eigenvector spectrums produced by the two methods.
基金Supported by the National Naturral Science Foundation of China(61301191)
文摘A full-polarimetric super-resolution algorithm with spatial smoothing processing is presented for one-dimensional（1-D）radar imaging.The coherence between scattering centers is minimized by using spatial smoothing processing（SSP）.Then the range and polarimetric scattering matrix of the scattering centers are estimated.The impact of different lengths of the smoothing window on the imaging quality is mainly analyzed with different signal-to-noise ratios（SNR）.Simulation and experimental results show that an improved radar super-resolution range profile and more precise estimation can be obtained by adjusting the length of the smoothing window under different SNR conditions.
文摘A novel method to estimate DOA of coherent signals impinging on a uniform circular array( UCA) is presented in this paper. A virtual uniform linear array (VULA) is first derived by using spatial DFT technique, transforming the UCA from element space to phase mode space to obtain the properties of ordinary ULA, and then the well known spatial smoothing technique is applied to the VULA so that the lost rank of covariance matrix due to signal coherence can be retrieved. This method makes it feasible to use the simple MUSIC algorithm to estimate DOA of coherent signals impinging on a UCA without heavy computation burden. Simulation results strongly verify the effectiveness of the algorithm.
基金Supported by the National Natural Science Foundation of China(61331019)
文摘The performance the quaternion-Capon（ Q-Capon） beamformer degraded when suppressing the interferences that are coherent with the signal of interest（ SOI）. To tackle the problem,the spatial smoothing technique is adopted in quaternion domain to decorrelate the interferences by using linearly and uniformly spaced two-component electromagnetic vector-sensors. By averaging several translational invariant subarray quaternion covariance matrices,the quaternion spatial smoothing is performed to prevent the SOI cancellation phenomena caused by the presence of coherent interferences. It is demonstrated that the quaternion spatial smoothing Q-Capon beamformer can suppress the coherent interferences remarkably while the computational cost is lower than the complex domain long vector spatial smoothing counterpart. Theoretical analyses and simulation results validate the efficacy of the spatially smoothed Q-Capon beamformer in terms of coherent interference suppression capability.
基金funded by the Special Fund for Fundamental Research of Central-level Public Interest Institutions,China(ZDJ2011-13)
文摘In this study, the North China seismic region was selected as the study area, and evaluation of seismic hazard using the spatial smoothing seismicity model was performed. Firstly, the study area is divided into grids, and some parameters （e. g. b-value, Mo, Me, azimuth and M-L relationship ） for each seismotectonic model were assigned. Secondly, using elliptical smoothing based on a seismotectonic background model, the statistical earthquake incidence rate in each grid is successively calculated. Lastly, the relevant ground motion attenuation relationship is chosen to assess seismic hazard of general sites. The maps for the distribution of horizontal peak ground acceleration with 10% probability of exceedance in 50 years were obtained by using the seismic hazard analysis method based on grid source. This seismicity model simplifies the methodology of probabilistic seismic hazard analysis, especially appropriate for those places where seismic tectonics is not yet clearly known. This method can provide valuable references for seismic zonation and seismic safety assessment for significant engineering projects.
基金supported by the National Key R&D Program of China(No.2022YFC3003502).
文摘The northern segment of the North-South Seismic Belt is characterized by intense crustal deformation,well-developed active tectonics,and frequent occurrences of strong earthquakes.Therefore,conducting a Probabilistic Seismic Hazard Analysis(PSHA)for this region is of significant importance for supporting seismic fortification in major engineering projects and formulating disaster prevention and mitigation policies.In this study,a composite seismic source model was constructed by integrating data on historical earthquakes,active faults,and paleoseismicity.Furthermore,a logic tree framework was employed to quantify epistemic uncertainties,enabling a systematic seismic hazard assessment of the region.To more accurately characterize the spatial heterogeneity of seismic activity,improvements were made to both the Circular Spatial Smoothing Model(CSSM)with a fixed radius and the Adaptive Spatial Smoothing Model(ASSM),with full consideration given to the spatiotemporal completeness of historical earthquake magnitudes.Regarding the CSSM,for scenarios involving small sample sizes in earthquake catalogs,the cross-validation method proposed in this study demonstrated higher robustness than the maximum likelihood method in determining the optimal correlation distance.Performance evaluation results indicate that while both models effectively characterize seismic activity,the ASSM exhibits superior overall predictive performance compared to the CSSM,owing to its ability to adaptively adjust the smoothing radius according to seismic density.Significant discrepancies were observed in the Peak Ground Acceleration(PGA)results calculated with a 10%probability of exceedance in 50 years across different combinations of seismic source models.The single spatially smoothed point-source model yielded a maximum PGA of approximately 0.52 g,with high-value areas concentrated near historical epicenters,thereby significantly underestimating the hazard associated with major fault zones.When combined with the simple fault-source model,the maximum PGA increased to 0.8 g,with high-value zones exhibiting a zonal distribution along faults;however,the risk remained underestimated for faults with low slip rates that are nevertheless approaching their recurrence cycles.Following the introduction of the time-dependent characteristic fault-source model,local PGA values for faults in the middle-to-late stages of their recurrence cycles increased by a factor of 2 to 7 compared to the single model.These results demonstrate that the characteristic fault-source model reasonably delineates the time-dependence of large earthquake recurrence,thereby providing a more accurate assessment of imminent seismic risks.By comprehensively applying the improved spatially smoothed pointsource model,the simple fault-source model,and the characteristic fault-source model,the following faults within the region were identified as having high seismic hazard:the Huangxianggou,Zhangxian,and Tianshui segments of the Xiqinling northern edge fault;the Maqin-Maqu segment of the Dongkunlun fault;the Longriqu fault;the Maoergai fault;the Elashan fault;the Riyueshan fault;the eastern segment of the Lenglongling fault;the Maxianshan segment of the Maxianshan northern Margin fault;and the Maomaoshan-Jinqianghe segment of the Laohushan-Maomaoshan fault.As these faults are located within seismic gaps or are approaching the recurrence periods of large earthquakes,they should be prioritized for current and future seismic monitoring as well as disaster prevention and mitigation efforts.
基金This work is supported by the Natural Science Foundation of China(NSFC Grant No.51808192,51879091,41630638)the Natural Science Foundation of Jiangsu Province(Grant No.BK20170887)the China Postdoctoral Science Foundation(Grant Nos.2017M611673 and 2018T110432).We thank Ms.Ruihua Yu for her contribution in compiling some of the figures in this work.
文摘This study proposed a random Smoothed Particle Hydrodynamics method for analyzing the post-failure behavior of landslides,which is based on the Karhunen-Loeve(K-L) expansion,the non-Newtonian fluid model,and the OpenMP parallel framework.Then,the applicability of this method was validated by comparing the generated random field with theoretical result and by simulating the post-failure process of an actual landslide.Thereafter,an illustrative landslide example was created and simulated to obtain the spatial variability effect of internal friction angle on the post-failure behavior of landslides under different coefficients of variation(COVs) and correlation lengths(CLs).As a conclusion,the reinforcement with materials of a larger friction angle can reduce the runout distance and impact the force of a landslide.As the increase of COV,the distribution range of influence zones also increases,which indicates that the deviation of influence zones becomes large.In addition,the correlation length in Monte Carlo simulations should not be too small,otherwise the variation range of influence zones will be underestimated.
文摘A novel correlation-based filter is presented for de-noising functional magnetic resonance imaging (fMRI) data.Temporal correlation-based exponential weights are defined for spatial smoothing of the data,with bias reduction using estimated noise variance.The proposed scheme is tested on simulated and real fMRI data.Finally,the results are compared with conventional filters.The method is found to be effectively suppressing the Rician noise in fMRI data,while improving the SNR.
文摘Spatial modeling has largely been applied in epidemiology and disease modeling. Different methods such as Generalized linear models (GLMs) have been made available to prediction of the claim frequencies. However, due to heterogeneity nature of policies, the methods do not generate precise and accurate claim frequencies predictions;these parametric statistical methods extensively depend on limiting assumptions (linearity, normality, independence among predictor variables, and a pre-existing functional form relating the criterion variable and predictive variables). This study investigates how to derive a spatial nonparametric model estimator based on smoothing Spline for predicting claim frequencies. The simulation results showed that the proposed estimator is efficient for prediction of claim frequencies than the kernel based counterpart. The estimator derived was applied to a sample of 6500 observations obtained from Cooperative Insurance Company, Kenya for the period of 2018-2020 and the results showed that the proposed method perform<span style="font-family:Verdana;">s</span><span style="font-family:Verdana;"> better than the kernel based counterpart. It is worth noting that inclusion of the spatial effects significantly improves the estimator prediction of claim frequency.</span>
文摘叶端定时是航空发动机叶片叶端振动非接触测量的有效手段,但其采样模式决定了所采信号具有高度欠采样特征,需要进行抗混叠频谱分析从而提取转子叶片固有频率这一关键指标。利用了前向平滑策略的改进多重信号分类法(multiple sIgnal classification,MUSIC)能实现抗混叠但无法充分发挥平滑方法的优势。因此,提出适用于叶端定时信号处理的前后向平滑MUSIC法,通过建立传感器的对称布局条件,利用前后向平滑方法代替前向平滑方法,得到更准确的自相关矩阵估计,进而提高叶片固有频率估计性能,并通过仿真和试验验证了在样本数量、算法参数等相同的情况下,前后向平滑MUSIC法的混叠与噪声抑制能力得到了提升。
基金supported by the National Basic Research(973)Program(2015CB351702)the National Natural Science Foundation of China(81571756,81270023,81278412,81171409,81000583,81471740,81220108014)+2 种基金Beijing Nova Program(XXJH2015B079 to Z.Y.)the Outstanding Young Investigator Award of Institute of Psychology,Chinese Academy of Sciences(to Z.Y.)the Key Research Program and the Hundred Talents Program of the Chinese Academy of Sciences(KSZD-EW-TZ-002 to X.N.Z)
文摘Abstract A brain network consisting of two key parietal nodes, the precuneus and the posterior cingulate cortex, has emerged from recent fMRI studies. Though it is anatomically adjacent to and spatially overlaps with the default mode network （DMN）, its function has been associated with memory processing, and it has been referred to as the parietal memory network （PMN）. Independent component analysis （ICA） is the most common data-driven method used to extract PMN and DMN simultaneously. However, the effects of data preprocessing and parameter determi- nation in ICA on PMN-DMN segregation are completely unknown. Here, we employ three typical algorithms of group ICA to assess how spatial smoothing and model order influence the degree of PMN-DMN segregation. Our findings indicate that PMN and DMN can only be stably separated using a combination of low-level spatial smoothing and high model order across the three ICA algorithms. We thus argue for more considerations on parametric settings for interpreting DMN data.
