Linear minimum mean square error(MMSE)detection has been shown to achieve near-optimal performance for massive multiple-input multiple-output(MIMO)systems but inevitably involves complicated matrix inversion,which ent...Linear minimum mean square error(MMSE)detection has been shown to achieve near-optimal performance for massive multiple-input multiple-output(MIMO)systems but inevitably involves complicated matrix inversion,which entails high complexity.To avoid the exact matrix inversion,a considerable number of implicit and explicit approximate matrix inversion based detection methods is proposed.By combining the advantages of both the explicit and the implicit matrix inversion,this paper introduces a new low-complexity signal detection algorithm.Firstly,the relationship between implicit and explicit techniques is analyzed.Then,an enhanced Newton iteration method is introduced to realize an approximate MMSE detection for massive MIMO uplink systems.The proposed improved Newton iteration significantly reduces the complexity of conventional Newton iteration.However,its complexity is still high for higher iterations.Thus,it is applied only for first two iterations.For subsequent iterations,we propose a novel trace iterative method(TIM)based low-complexity algorithm,which has significantly lower complexity than higher Newton iterations.Convergence guarantees of the proposed detector are also provided.Numerical simulations verify that the proposed detector exhibits significant performance enhancement over recently reported iterative detectors and achieves close-to-MMSE performance while retaining the low-complexity advantage for systems with hundreds of antennas.展开更多
In the preliminary design stage of the full form ships, in order to obtain a hull form with low resistance and maximum propulsion efficiency, an optimization design program for a full form ship with the minimum thrust...In the preliminary design stage of the full form ships, in order to obtain a hull form with low resistance and maximum propulsion efficiency, an optimization design program for a full form ship with the minimum thrust deduction factor has been developed, which combined the potential flow theory and boundary layer theory with the optimization technique. In the optimization process, the Sequential Unconstrained Minimization Technique(SUMT) interior point method of Nonlinear Programming(NLP) was proposed with the minimum thrust deduction factor as the objective function. An appropriate displacement is a basic constraint condition, and the boundary layer separation is an additional one. The parameters of the hull form modification function are used as design variables. At last, the numerical optimization example for lines of after-body of 50000 DWT product oil tanker was provided, which indicated that the propulsion efficiency was improved distinctly by this optimal design method.展开更多
To overcome the shortcoming that the traditional minimum error threshold method can obtain satisfactory image segmentation results only when the object and background of the image strictly obey a certain type of proba...To overcome the shortcoming that the traditional minimum error threshold method can obtain satisfactory image segmentation results only when the object and background of the image strictly obey a certain type of probability distribution,one proposes the regularized minimum error threshold method and treats the traditional minimum error threshold method as its special case.Then one constructs the discrete probability distribution by using the separation between segmentation threshold and the average gray-scale values of the object and background of the image so as to compute the information energy of the probability distribution.The impact of the regularized parameter selection on the optimal segmentation threshold of the regularized minimum error threshold method is investigated.To verify the effectiveness of the proposed regularized minimum error threshold method,one selects typical grey-scale images and performs segmentation tests.The segmentation results obtained by the regularized minimum error threshold method are compared with those obtained with the traditional minimum error threshold method.The segmentation results and their analysis show that the regularized minimum error threshold method is feasible and produces more satisfactory segmentation results than the minimum error threshold method.It does not exert much impact on object acquisition in case of the addition of a certain noise to an image.Therefore,the method can meet the requirements for extracting a real object in the noisy environment.展开更多
The wireline formation tester (WFT) is an important tool for formation evaluation, such as calculating the formation pressure and permeability, identifying the fluid type, and determining the interface between oil a...The wireline formation tester (WFT) is an important tool for formation evaluation, such as calculating the formation pressure and permeability, identifying the fluid type, and determining the interface between oil and water. However, in a low porosity and low permeability formation, the supercharge pressure effect exists, since the mudcake has a poor sealing ability. The mudcake cannot isolate the hydrostatic pressure of the formation around the borehole and the mud seeps into the formations, leading to inaccurate formation pressure measurement. At the same time, the tool can be easily stuck in the low porosity/low permeability formation due to the long waiting and testing time. We present a method for determining the minimum testing time for the wireline formation tester. The pressure distribution of the mudcake and the formation were respectively calculated with the finite element method (FEM). The radius of the influence of mud pressure was also computed, and the minimum testing time in low porosity/low permeability formations was determined within a range of values for different formation permeabilities. The determination of the minimum testing time ensures an accurate formation pressure measurement and minimizes possible accidents due to long waiting and testing time.展开更多
In case of heteroscedasticity, a Generalized Minimum Perpendicular Distance Square (GMPDS) method has been suggested instead of traditionally used Generalized Least Square (GLS) method to fit a regression line, with a...In case of heteroscedasticity, a Generalized Minimum Perpendicular Distance Square (GMPDS) method has been suggested instead of traditionally used Generalized Least Square (GLS) method to fit a regression line, with an aim to get a better fitted regression line, so that the estimated line will be closest one to the observed points. Mathematical form of the estimator for the parameters has been presented. A logical argument behind the relationship between the slopes of the lines and has been placed.展开更多
MDM (minimum distance method) is a very popular algorithm in staterecognition. But it has a presupposition, that is, the distance within one class must be shorterenough than the distance between classes. When this pre...MDM (minimum distance method) is a very popular algorithm in staterecognition. But it has a presupposition, that is, the distance within one class must be shorterenough than the distance between classes. When this presupposition is not satisfied, the method isno longer valid. In order to overcome the shortcomings of MDM, an improved minimum distance method(IMDM) based on ANN (artificial neural networks) is presented. The simulation results demonstratethat IMDM has two advantages, that is, the rate of recognition is faster and the accuracy ofrecognition is higher compared with MDM.展开更多
The evaluation of the minimum distance of linear block codes remains an open problem in coding theory, and it is not easy to determine its true value by classical methods, for this reason the problem has been solved i...The evaluation of the minimum distance of linear block codes remains an open problem in coding theory, and it is not easy to determine its true value by classical methods, for this reason the problem has been solved in the literature with heuristic techniques such as genetic algorithms and local search algorithms. In this paper we propose two approaches to attack the hardness of this problem. The first approach is based on genetic algorithms and it yield to good results comparing to another work based also on genetic algorithms. The second approach is based on a new randomized algorithm which we call 'Multiple Impulse Method (MIM)', where the principle is to search codewords locally around the all-zero codeword perturbed by a minimum level of noise, anticipating that the resultant nearest nonzero codewords will most likely contain the minimum Hamming-weight codeword whose Hamming weight is equal to the minimum distance of the linear code.展开更多
综合能源系统(integrated energy system,IES)作为能源转型中的重要环节已得到越来越多国家的广泛关注。构建一套匹配中国国情的综合能源系统评价体系和评价方法不仅能够为综合能源系统规划后评价打下基础,以此对规划方案进行优劣排序;...综合能源系统(integrated energy system,IES)作为能源转型中的重要环节已得到越来越多国家的广泛关注。构建一套匹配中国国情的综合能源系统评价体系和评价方法不仅能够为综合能源系统规划后评价打下基础,以此对规划方案进行优劣排序;还能够提高综合能源系统项目的管理水平,在制定统一、完整的综合能源系统综合评价标准时提供参考。为此,首先结合园区IES基本特征以及运行特性,构建包含经济性、可靠性、环保性以及智能友好性4个方面的综合评价指标体系;然后为解决IES在运行中的不确定性问题,对基于传统云物元模型的综合评价体系提出云熵优化,即考虑不同评价者对模糊性的可接受程度;为解决单一赋权方法可能导致的评价结果过于主观或过于客观的问题,选择基于最小鉴别信息原理将决策实验室法与熵权法相结合的综合赋权法,并采用变权法进一步完善综合评价指标;最后通过算例分析,验证所提综合评价体系的科学正确性。展开更多
The intersection method is one of the basic approaches for locating earthquakes and is not only robust but also efficient. However, its location accuracy is not high, especially for focal depth because the velocity mo...The intersection method is one of the basic approaches for locating earthquakes and is not only robust but also efficient. However, its location accuracy is not high, especially for focal depth because the velocity model used for the conventional intersection method is based on homogeneous or laterally homogeneous media, which is too simple. In order to improve the accuracy, we have modified the existing intersection method. In the modified approach, the earthquake loci are not assumed to be circular or hyperbolic and calculation accuracy is improved using a minimum traveltime tree algorithm for tracing rays. The numerical model shows that the modified method can locate earthquakes in complex velocity models.展开更多
基金supported by National Natural Science Foundation of China(62371225,62371227)。
文摘Linear minimum mean square error(MMSE)detection has been shown to achieve near-optimal performance for massive multiple-input multiple-output(MIMO)systems but inevitably involves complicated matrix inversion,which entails high complexity.To avoid the exact matrix inversion,a considerable number of implicit and explicit approximate matrix inversion based detection methods is proposed.By combining the advantages of both the explicit and the implicit matrix inversion,this paper introduces a new low-complexity signal detection algorithm.Firstly,the relationship between implicit and explicit techniques is analyzed.Then,an enhanced Newton iteration method is introduced to realize an approximate MMSE detection for massive MIMO uplink systems.The proposed improved Newton iteration significantly reduces the complexity of conventional Newton iteration.However,its complexity is still high for higher iterations.Thus,it is applied only for first two iterations.For subsequent iterations,we propose a novel trace iterative method(TIM)based low-complexity algorithm,which has significantly lower complexity than higher Newton iterations.Convergence guarantees of the proposed detector are also provided.Numerical simulations verify that the proposed detector exhibits significant performance enhancement over recently reported iterative detectors and achieves close-to-MMSE performance while retaining the low-complexity advantage for systems with hundreds of antennas.
基金financially supported by the National Natural Science Foundation of China(Grant No.51009087)
文摘In the preliminary design stage of the full form ships, in order to obtain a hull form with low resistance and maximum propulsion efficiency, an optimization design program for a full form ship with the minimum thrust deduction factor has been developed, which combined the potential flow theory and boundary layer theory with the optimization technique. In the optimization process, the Sequential Unconstrained Minimization Technique(SUMT) interior point method of Nonlinear Programming(NLP) was proposed with the minimum thrust deduction factor as the objective function. An appropriate displacement is a basic constraint condition, and the boundary layer separation is an additional one. The parameters of the hull form modification function are used as design variables. At last, the numerical optimization example for lines of after-body of 50000 DWT product oil tanker was provided, which indicated that the propulsion efficiency was improved distinctly by this optimal design method.
基金supported by the National Natural Science Foundations of China(Nos.61136002,61472324)the Natural Science Foundation of Shanxi Province(No.2014JM8331)
文摘To overcome the shortcoming that the traditional minimum error threshold method can obtain satisfactory image segmentation results only when the object and background of the image strictly obey a certain type of probability distribution,one proposes the regularized minimum error threshold method and treats the traditional minimum error threshold method as its special case.Then one constructs the discrete probability distribution by using the separation between segmentation threshold and the average gray-scale values of the object and background of the image so as to compute the information energy of the probability distribution.The impact of the regularized parameter selection on the optimal segmentation threshold of the regularized minimum error threshold method is investigated.To verify the effectiveness of the proposed regularized minimum error threshold method,one selects typical grey-scale images and performs segmentation tests.The segmentation results obtained by the regularized minimum error threshold method are compared with those obtained with the traditional minimum error threshold method.The segmentation results and their analysis show that the regularized minimum error threshold method is feasible and produces more satisfactory segmentation results than the minimum error threshold method.It does not exert much impact on object acquisition in case of the addition of a certain noise to an image.Therefore,the method can meet the requirements for extracting a real object in the noisy environment.
文摘The wireline formation tester (WFT) is an important tool for formation evaluation, such as calculating the formation pressure and permeability, identifying the fluid type, and determining the interface between oil and water. However, in a low porosity and low permeability formation, the supercharge pressure effect exists, since the mudcake has a poor sealing ability. The mudcake cannot isolate the hydrostatic pressure of the formation around the borehole and the mud seeps into the formations, leading to inaccurate formation pressure measurement. At the same time, the tool can be easily stuck in the low porosity/low permeability formation due to the long waiting and testing time. We present a method for determining the minimum testing time for the wireline formation tester. The pressure distribution of the mudcake and the formation were respectively calculated with the finite element method (FEM). The radius of the influence of mud pressure was also computed, and the minimum testing time in low porosity/low permeability formations was determined within a range of values for different formation permeabilities. The determination of the minimum testing time ensures an accurate formation pressure measurement and minimizes possible accidents due to long waiting and testing time.
文摘In case of heteroscedasticity, a Generalized Minimum Perpendicular Distance Square (GMPDS) method has been suggested instead of traditionally used Generalized Least Square (GLS) method to fit a regression line, with an aim to get a better fitted regression line, so that the estimated line will be closest one to the observed points. Mathematical form of the estimator for the parameters has been presented. A logical argument behind the relationship between the slopes of the lines and has been placed.
基金This work was financially supported by the National Natural Science Foundation of China under the contract No.69372031.]
文摘MDM (minimum distance method) is a very popular algorithm in staterecognition. But it has a presupposition, that is, the distance within one class must be shorterenough than the distance between classes. When this presupposition is not satisfied, the method isno longer valid. In order to overcome the shortcomings of MDM, an improved minimum distance method(IMDM) based on ANN (artificial neural networks) is presented. The simulation results demonstratethat IMDM has two advantages, that is, the rate of recognition is faster and the accuracy ofrecognition is higher compared with MDM.
文摘The evaluation of the minimum distance of linear block codes remains an open problem in coding theory, and it is not easy to determine its true value by classical methods, for this reason the problem has been solved in the literature with heuristic techniques such as genetic algorithms and local search algorithms. In this paper we propose two approaches to attack the hardness of this problem. The first approach is based on genetic algorithms and it yield to good results comparing to another work based also on genetic algorithms. The second approach is based on a new randomized algorithm which we call 'Multiple Impulse Method (MIM)', where the principle is to search codewords locally around the all-zero codeword perturbed by a minimum level of noise, anticipating that the resultant nearest nonzero codewords will most likely contain the minimum Hamming-weight codeword whose Hamming weight is equal to the minimum distance of the linear code.
文摘综合能源系统(integrated energy system,IES)作为能源转型中的重要环节已得到越来越多国家的广泛关注。构建一套匹配中国国情的综合能源系统评价体系和评价方法不仅能够为综合能源系统规划后评价打下基础,以此对规划方案进行优劣排序;还能够提高综合能源系统项目的管理水平,在制定统一、完整的综合能源系统综合评价标准时提供参考。为此,首先结合园区IES基本特征以及运行特性,构建包含经济性、可靠性、环保性以及智能友好性4个方面的综合评价指标体系;然后为解决IES在运行中的不确定性问题,对基于传统云物元模型的综合评价体系提出云熵优化,即考虑不同评价者对模糊性的可接受程度;为解决单一赋权方法可能导致的评价结果过于主观或过于客观的问题,选择基于最小鉴别信息原理将决策实验室法与熵权法相结合的综合赋权法,并采用变权法进一步完善综合评价指标;最后通过算例分析,验证所提综合评价体系的科学正确性。
基金This work is supported by the National Natural Science Foundation of China(40674044)the Special Foundation for Basic Professional Scientific Research (DQJB06A02)
文摘The intersection method is one of the basic approaches for locating earthquakes and is not only robust but also efficient. However, its location accuracy is not high, especially for focal depth because the velocity model used for the conventional intersection method is based on homogeneous or laterally homogeneous media, which is too simple. In order to improve the accuracy, we have modified the existing intersection method. In the modified approach, the earthquake loci are not assumed to be circular or hyperbolic and calculation accuracy is improved using a minimum traveltime tree algorithm for tracing rays. The numerical model shows that the modified method can locate earthquakes in complex velocity models.