The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the...The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the equivalent conditions of complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space.The results complement the corresponding results in probability space to those for sequences of independent,identically distributed random variables under sublinear expectation space.展开更多
This paper proposes a reliability evaluation model for a multi-dimensional network system,which has potential to be applied to the internet of things or other practical networks.A multi-dimensional network system with...This paper proposes a reliability evaluation model for a multi-dimensional network system,which has potential to be applied to the internet of things or other practical networks.A multi-dimensional network system with one source element and multiple sink elements is considered first.Each element can con-nect with other elements within a stochastic connection ranges.The system is regarded as successful as long as the source ele-ment remains connected with all sink elements.An importance measure is proposed to evaluate the performance of non-source elements.Furthermore,to calculate the system reliability and the element importance measure,a multi-valued decision diagram based approach is structured and its complexity is analyzed.Finally,a numerical example about the signal transfer station system is illustrated to analyze the system reliability and the ele-ment importance measure.展开更多
In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergen...In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergence of NSD random variables.We establish and improve a general result on the complete f-moment convergence for Sung’s type randomly weighted sums of NSD random variables under some general assumptions.As an application,we show the complete consistency for the randomly weighted estimator in a nonparametric regression model based on NSD errors.展开更多
In this paper,we investigate the complete convergence and complete moment conver-gence for weighted sums of arrays of rowwise asymptotically negatively associated(ANA)random variables,without assuming identical distri...In this paper,we investigate the complete convergence and complete moment conver-gence for weighted sums of arrays of rowwise asymptotically negatively associated(ANA)random variables,without assuming identical distribution.The obtained results not only extend those of An and Yuan[1]and Shen et al.[2]to the case of ANA random variables,but also partially improve them.展开更多
We consider a single server constant retrial queue,in which a state-dependent service policy is used to control the service rate.Customer arrival follows Poisson process,while service time and retrial time are exponen...We consider a single server constant retrial queue,in which a state-dependent service policy is used to control the service rate.Customer arrival follows Poisson process,while service time and retrial time are exponential distributions.Whenever the server is available,it admits the retrial customers into service based on a first-come first-served rule.The service rate adjusts in real-time based on the retrial queue length.An iterative algorithm is proposed to numerically solve the personal optimal problem in the fully observable scenario.Furthermore,we investigate the impact of parameters on the social optimal threshold.The effectiveness of the results is illustrated by two examples.展开更多
Aiming at the concept of ＂diagnosis＂, a simple and effective broadband radar cross section （RCS） measurement system is constructed, and some multi-dimensional scattering properties diagnosis techniques are present...Aiming at the concept of ＂diagnosis＂, a simple and effective broadband radar cross section （RCS） measurement system is constructed, and some multi-dimensional scattering properties diagnosis techniques are presented based on the system. Firstly, a stepped-frequency signal is employed to achieve high range resolution, combining with a variety of signal processing tech- niques. Secondly, cross-range resolution is gained with a rotating table, and the high-resolution two-dimensional （2-D） imaging of the scale model is obtained by the microwave imaging theory. Finally, two receiving antennas with a small distance in altitude are used, and the three-dimensional （3-D） height distribution of scattering points on the scale model is extracted from the phase of images. Some typical bodies and a scale aircraft model are diagnosed in an anechoic chamber. The experimental results show that, after scaling with a metal sphere, the accurate one- dimensional （l-D） RCS pattern of the model is obtained, and it has a large dynamic range. When the bandwidth of the transmitting signal is 4 GHz, the resolution of the 2-D image can reach to 0.037 5 m. The 3-D height distribution of scattering points is given by interferometric measurement. This paper provides a feasible way to obtain high-precision scattering properties parameters of the scale aircraft model in a conventional rectangular anechoic chamber.展开更多
Traditional data envelopment analysis（DEA） theory assumes that decision variables are regarded as inputs or outputs,and no variable can play the roles of both an input and an output at the same time.In fact,there ex...Traditional data envelopment analysis（DEA） theory assumes that decision variables are regarded as inputs or outputs,and no variable can play the roles of both an input and an output at the same time.In fact,there exist some variables that work as inputs and outputs simultaneously and are called dual-role variables.Traditional DEA models cannot be used to appraise the performance of decision making units containing dual-role variables.The paper analyzes the structure and properties of the production systems comprising dual-role variables,and proposes a DEA model integrating dual-role variables.Finally the proposed model is illustrated to evaluate the efficiency of university departments.展开更多
In winter, the confined pig house of northern China is severe. The environment variables are nonlinear, time-varying and coupled, which seriously affect the health of pigs and the qualities of the meat. In order to so...In winter, the confined pig house of northern China is severe. The environment variables are nonlinear, time-varying and coupled, which seriously affect the health of pigs and the qualities of the meat. In order to solve the problem multi-variables coupling, a multi-variables decoupled fuzzy logic control method was proposed. Two fuzzy logic controllers were designed based on fuzzy logic theory. The fans, heaters and humidifiers were used to control temperature, humidity and ammonia. The reductions of temperature and humidity caused by ventilating were compensated by heaters and humidifiers respectively which realized the multivariables decoupling. The proposed methods were validated through theoretical, experimental and simulation analysis. The results suggested that the methods were able to regulate the confined pig house environment effectively. In addition, comparing to the manual regulation, the proposed methods could reduce 19% power consumption as well.展开更多
The fatigue life of aeroengine turbine disc presents great dispersion due to the randomness of the basic variables,such as applied load,working temperature,geometrical dimensions and material properties.In order to am...The fatigue life of aeroengine turbine disc presents great dispersion due to the randomness of the basic variables,such as applied load,working temperature,geometrical dimensions and material properties.In order to ameliorate reliability analysis efficiency without loss of reliability,the distributed collaborative response surface method(DCRSM) was proposed,and its basic theories were established in this work.Considering the failure dependency among the failure modes,the distributed response surface was constructed to establish the relationship between the failure mode and the relevant random variables.Then,the failure modes were considered as the random variables of system response to obtain the distributed collaborative response surface model based on structure failure criterion.Finally,the given turbine disc structure was employed to illustrate the feasibility and validity of the presented method.Through the comparison of DCRSM,Monte Carlo method(MCM) and the traditional response surface method(RSM),the results show that the computational precision for DCRSM is more consistent with MCM than RSM,while DCRSM needs far less computing time than MCM and RSM under the same simulation conditions.Thus,DCRSM is demonstrated to be a feasible and valid approach for improving the computational efficiency of reliability analysis for aeroengine turbine disc fatigue life with multiple random variables,and has great potential value for the complicated mechanical structure with multi-component and multi-failure mode.展开更多
This work aims to provide a relationship of how the key operational variables of frother type and impeller speed affect the size of bubble （D32）. The study was performed using pilot-scale equipment （0.8 m^3） that ...This work aims to provide a relationship of how the key operational variables of frother type and impeller speed affect the size of bubble （D32）. The study was performed using pilot-scale equipment （0.8 m^3） that is up to two orders of magnitude larger than equipment used for studies performed to date by others, and incorporated the key process variables of frother type and impeller speed. The results show that each frother family exhibits a unique CCC95-HLB relationship dependent on n （number of C-atoms in alkyl group） and m （number of propylene oxide group）. Empirical models were developed to predict CCC95 from HLB associated with other two parameters a and ft. The impeller speed-bubble size tests show that D32 is unaffected by increased impeller tip speed across the range of 4.6 to 9.2 m/s （representing the industrial operating range）, although D32 starts to increase below 4.6 m/s. The finding is valid for both coalescing and non-coalescing conditions. The results suggest that the bubble size and bubble size distribution （BSD） being created do not change with increasing impeller speed in the quiescent zone of the flotation.展开更多
Intercepted signal blind separation is a research topic with high importance for both military and civilian communication systems. A blind separation method for space-time block code （STBC） systems is proposed by us...Intercepted signal blind separation is a research topic with high importance for both military and civilian communication systems. A blind separation method for space-time block code （STBC） systems is proposed by using the ordinary independent component analysis （ICA）. This method cannot work when specific complex modulations are employed since the assumption of mutual independence cannot be satisfied. The analysis shows that source signals, which are group-wise independent and use multi-dimensional ICA （MICA） instead of ordinary ICA, can be applied in this case. Utilizing the block-diagonal structure of the cumulant matrices, the JADE algorithm is generalized to the multidimensional case to separate the received data into mutually independent groups. Compared with ordinary ICA algorithms, the proposed method does not introduce additional ambiguities. Simulations show that the proposed method overcomes the drawback and achieves a better performance without utilizing coding information than channel estimation based algorithms.展开更多
A new algorithm using orthogonal polynomials and sample moments was presented for estimating probability curves directly from experimental or field data of rock variables. The moments estimated directly from a sample ...A new algorithm using orthogonal polynomials and sample moments was presented for estimating probability curves directly from experimental or field data of rock variables. The moments estimated directly from a sample of observed values of a random variable could be conventional moments (moments about the origin or central moments) and probability-weighted moments (PWMs). Probability curves derived from orthogonal polynomials and conventional moments are probability density functions (PDF), and probability curves derived from orthogonal polynomials and PWMs are inverse cumulative density functions (CDF) of random variables. The proposed approach is verified by two most commonly-used theoretical standard distributions: normal and exponential distribution. Examples from observed data of uniaxial compressive strength of a rock and concrete strength data are presented for illustrative purposes. The results show that probability curves of rock variable can be accurately derived from orthogonal polynomials and sample moments. Orthogonal polynomials and PWMs enable more secure inferences to be made from relatively small samples about an underlying probability curve.展开更多
In the field of weapon system of systems (WSOS) simulation, various indicators are widely used to describe the capability of WSOS, but it is always difficult to describe the comprehensive capability of WSOS quickly an...In the field of weapon system of systems (WSOS) simulation, various indicators are widely used to describe the capability of WSOS, but it is always difficult to describe the comprehensive capability of WSOS quickly and intuitively by visualization of multi-dimensional indicators. A method of machine learning and visualization is proposed, which can display and analyze the capabilities of different WSOS in a two-dimensional plane. The analysis and comparison of the comprehensive capability of different components of WSOS is realized by the method, which consists of six parts: multiple simulations, key indicators mining, three spatial distance calculation, fusion project calculation, calculation of individual capability density, and calculation of multiple capability ranges overlay. Binding a simulation experiment, the collaborative analysis of six indicators and 100 possible kinds of red WSOS are achieved. The experimental results show that this method can effectively improve the quality and speed of capabilities analysis, reveal a large number of potential information, and provide a visual support for the qualitative and quantitative analysis model.展开更多
A method is proposed to deal with the uncertain multiple attribute group decision making problems,where 2-dimension uncertain linguistic variables(2DULVs)are used as the reliable way for the experts to express their f...A method is proposed to deal with the uncertain multiple attribute group decision making problems,where 2-dimension uncertain linguistic variables(2DULVs)are used as the reliable way for the experts to express their fuzzy subjective evaluation information.Firstly,in order to measure the 2DULVs more accurately,a new method is proposed to compare two 2DULVs,called a score function,while a new function is defined to measure the distance between two 2DULVs.Secondly,two optimization models are established to determine the weight of experts and attributes based on the new distance formula and a weighted average operator is used to determine the comprehensive evaluation value of each alternative.Then,a score function is used to determine the ranking of the alternatives.Finally,the effectiveness of the proposed method is proved by an illustrated example.展开更多
In order to improve the accuracy of biophysical parameters retrieved from remotely sensing data, a new algorithm was presented by using spatial contextual to estimate canopy variables from high-resolution remote sensi...In order to improve the accuracy of biophysical parameters retrieved from remotely sensing data, a new algorithm was presented by using spatial contextual to estimate canopy variables from high-resolution remote sensing images. The developed algorithm was used for inversion of leaf area index (LAI) from Enhanced Thematic Mapper Plus (ETM+) data by combining with optimization method to minimize cost functions. The results show that the distribution of LAI is spatially consistent with the false composition imagery from ETM+ and the accuracy of LAI is significantly improved over the results retrieved by the conventional pixelwise retrieval methods, demonstrating that this method can be reliably used to integrate spatial contextual information for inverting LAI from high-resolution remote sensing images.展开更多
Input variables selection(IVS) is proved to be pivotal in nonlinear dynamic system modeling. In order to optimize the model of the nonlinear dynamic system, a fuzzy modeling method for determining the premise structur...Input variables selection(IVS) is proved to be pivotal in nonlinear dynamic system modeling. In order to optimize the model of the nonlinear dynamic system, a fuzzy modeling method for determining the premise structure by selecting important inputs of the system is studied. Firstly, a simplified two stage fuzzy curves method is proposed, which is employed to sort all possible inputs by their relevance with outputs, select the important input variables of the system and identify the structure.Secondly, in order to reduce the complexity of the model, the standard fuzzy c-means clustering algorithm and the recursive least squares algorithm are used to identify the premise parameters and conclusion parameters, respectively. Then, the effectiveness of IVS is verified by two well-known issues. Finally, the proposed identification method is applied to a realistic variable load pneumatic system. The simulation experiments indi cate that the IVS method in this paper has a positive influence on the approximation performance of the Takagi-Sugeno(T-S) fuzzy modeling.展开更多
Aiming at the phenomenon of discrete variables whic h generally exists in engineering structural optimization, a novel hybrid genetic algorithm (HGA) is proposed to directly search the optimal solution in this pape r....Aiming at the phenomenon of discrete variables whic h generally exists in engineering structural optimization, a novel hybrid genetic algorithm (HGA) is proposed to directly search the optimal solution in this pape r. The imitative full-stress design method (IFS) was presented for discrete struct ural optimum design subjected to multi-constraints. To reach the imitative full -stress state for dangerous members was the target of IFS through iteration. IF S is integrated in the GA. The basic idea of HGA is to divide the optimization t ask into two complementary parts. The coarse, global optimization is done by the GA while local refinement is done by IFS. For instance, every K generations, th e population is doped with a locally optimal individual obtained from IFS. Both methods run in parallel. All or some of individuals are continuously used as initial values for IFS. The locally optimized individuals are re-implanted into the current generation in the GA. From some numeral examples, hybridizatio n has been discovered as enormous potential for improvement of genetic algorit hm. Selection is the component which guides the HGA to the solution by preferring in dividuals with high fitness over low-fitted ones. Selection can be deterministi c operation, but in most implementations it has random components. "Elite surviv al" is introduced to avoid that the observed best-fitted individual dies out, j ust by selecting it for the next generation without any random experiments. The individuals of population are competitive only in the same generation. There exists no competition among different generations. So HGA may be permitted to h ave different evaluation criteria for different generations. Multi-Selectio n schemes are adopted to avoid slow refinement since the individuals have si milar fitness values in the end phase of HGA. The feasibility of this method is tested with examples of engineering design wit h discrete variables. Results demonstrate the validity of HGA.展开更多
Space-time coding radar has been recently proposed and investigated.It is a radar framework which can perform transmit beamforming at the receiver.However,the range resolution decreases when the number of the transmit...Space-time coding radar has been recently proposed and investigated.It is a radar framework which can perform transmit beamforming at the receiver.However,the range resolution decreases when the number of the transmit element increases.A subarray-based space-time coding(sub-STC)radar is explored to alleviate the range resolution reduction.For the proposed radar configuration,an identical waveform is transmitted and it introduces a small time offset in different subarrays.The multidimensional ambiguity function of sub-STC radar is defined by considering resolutions in multiple domains including the range,Doppler,angle and probing direction.Analyses on properties of the multi-dimensional ambiguity function of the sub-STC radar with regard to the spatial coverage,resolution performance and low sidelobes are also given.Results reveal that the range resolution and low sidelobes performance are improved with the proposed approach.展开更多
基金supported by Doctoral Scientific Research Starting Foundation of Jingdezhen Ceramic University(Grant No.102/01003002031)Re-accompanying Funding Project of Academic Achievements of Jingdezhen Ceramic University(Grant Nos.215/20506277,215/20506341)。
文摘The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the equivalent conditions of complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space.The results complement the corresponding results in probability space to those for sequences of independent,identically distributed random variables under sublinear expectation space.
基金supported by the National Natural Science Foundation of China(72101025,72271049),the Interdisciplinary Research Project for Young Teachers of USTB(Fundamental Research Funds for the Central Universities,FRF-IDRY-24-024)the Hebei Natural Science Foundation(F2023501011)+1 种基金the Fundamental Research Funds for the Central Universities(FRF-TP-20-073A1)the R&D Program of Beijing Municipal Education Commission(KM202411232015).
文摘This paper proposes a reliability evaluation model for a multi-dimensional network system,which has potential to be applied to the internet of things or other practical networks.A multi-dimensional network system with one source element and multiple sink elements is considered first.Each element can con-nect with other elements within a stochastic connection ranges.The system is regarded as successful as long as the source ele-ment remains connected with all sink elements.An importance measure is proposed to evaluate the performance of non-source elements.Furthermore,to calculate the system reliability and the element importance measure,a multi-valued decision diagram based approach is structured and its complexity is analyzed.Finally,a numerical example about the signal transfer station system is illustrated to analyze the system reliability and the ele-ment importance measure.
基金supported by the National Social Science Fundation(Grant No.21BTJ040)the Project of Outstanding Young People in University of Anhui Province(Grant Nos.2023AH020037,SLXY2024A001).
文摘In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergence of NSD random variables.We establish and improve a general result on the complete f-moment convergence for Sung’s type randomly weighted sums of NSD random variables under some general assumptions.As an application,we show the complete consistency for the randomly weighted estimator in a nonparametric regression model based on NSD errors.
基金National Natural Science Foundation of China (Grant Nos.12061028, 71871046)Support Program of the Guangxi China Science Foundation (Grant No.2018GXNSFAA281011)。
文摘In this paper,we investigate the complete convergence and complete moment conver-gence for weighted sums of arrays of rowwise asymptotically negatively associated(ANA)random variables,without assuming identical distribution.The obtained results not only extend those of An and Yuan[1]and Shen et al.[2]to the case of ANA random variables,but also partially improve them.
基金supported by the National Natural Science Foundation of China(Grant No.11971486)。
文摘We consider a single server constant retrial queue,in which a state-dependent service policy is used to control the service rate.Customer arrival follows Poisson process,while service time and retrial time are exponential distributions.Whenever the server is available,it admits the retrial customers into service based on a first-come first-served rule.The service rate adjusts in real-time based on the retrial queue length.An iterative algorithm is proposed to numerically solve the personal optimal problem in the fully observable scenario.Furthermore,we investigate the impact of parameters on the social optimal threshold.The effectiveness of the results is illustrated by two examples.
基金supported by the National Natural Science Foundation of China(6120132061371023)
文摘Aiming at the concept of ＂diagnosis＂, a simple and effective broadband radar cross section （RCS） measurement system is constructed, and some multi-dimensional scattering properties diagnosis techniques are presented based on the system. Firstly, a stepped-frequency signal is employed to achieve high range resolution, combining with a variety of signal processing tech- niques. Secondly, cross-range resolution is gained with a rotating table, and the high-resolution two-dimensional （2-D） imaging of the scale model is obtained by the microwave imaging theory. Finally, two receiving antennas with a small distance in altitude are used, and the three-dimensional （3-D） height distribution of scattering points on the scale model is extracted from the phase of images. Some typical bodies and a scale aircraft model are diagnosed in an anechoic chamber. The experimental results show that, after scaling with a metal sphere, the accurate one- dimensional （l-D） RCS pattern of the model is obtained, and it has a large dynamic range. When the bandwidth of the transmitting signal is 4 GHz, the resolution of the 2-D image can reach to 0.037 5 m. The 3-D height distribution of scattering points is given by interferometric measurement. This paper provides a feasible way to obtain high-precision scattering properties parameters of the scale aircraft model in a conventional rectangular anechoic chamber.
基金supported by the National Natural Science Foundation of China (7082100170801056)
文摘Traditional data envelopment analysis（DEA） theory assumes that decision variables are regarded as inputs or outputs,and no variable can play the roles of both an input and an output at the same time.In fact,there exist some variables that work as inputs and outputs simultaneously and are called dual-role variables.Traditional DEA models cannot be used to appraise the performance of decision making units containing dual-role variables.The paper analyzes the structure and properties of the production systems comprising dual-role variables,and proposes a DEA model integrating dual-role variables.Finally the proposed model is illustrated to evaluate the efficiency of university departments.
基金Supported by the 13th Five-year National Key R&D Program(2016YFD0700204-02)the"Young Talents"Project of Northeast Agricultural University(17QC20,17QC19)the Earmarked Fund for China Agriculture Research System(CARS-35)
文摘In winter, the confined pig house of northern China is severe. The environment variables are nonlinear, time-varying and coupled, which seriously affect the health of pigs and the qualities of the meat. In order to solve the problem multi-variables coupling, a multi-variables decoupled fuzzy logic control method was proposed. Two fuzzy logic controllers were designed based on fuzzy logic theory. The fans, heaters and humidifiers were used to control temperature, humidity and ammonia. The reductions of temperature and humidity caused by ventilating were compensated by heaters and humidifiers respectively which realized the multivariables decoupling. The proposed methods were validated through theoretical, experimental and simulation analysis. The results suggested that the methods were able to regulate the confined pig house environment effectively. In addition, comparing to the manual regulation, the proposed methods could reduce 19% power consumption as well.
基金Project(51335003)supported by the National Natural Science Foundation of ChinaProject(20111102110011)supported by the Specialized Research Fund for the Doctoral Program of Higher Education of China
文摘The fatigue life of aeroengine turbine disc presents great dispersion due to the randomness of the basic variables,such as applied load,working temperature,geometrical dimensions and material properties.In order to ameliorate reliability analysis efficiency without loss of reliability,the distributed collaborative response surface method(DCRSM) was proposed,and its basic theories were established in this work.Considering the failure dependency among the failure modes,the distributed response surface was constructed to establish the relationship between the failure mode and the relevant random variables.Then,the failure modes were considered as the random variables of system response to obtain the distributed collaborative response surface model based on structure failure criterion.Finally,the given turbine disc structure was employed to illustrate the feasibility and validity of the presented method.Through the comparison of DCRSM,Monte Carlo method(MCM) and the traditional response surface method(RSM),the results show that the computational precision for DCRSM is more consistent with MCM than RSM,while DCRSM needs far less computing time than MCM and RSM under the same simulation conditions.Thus,DCRSM is demonstrated to be a feasible and valid approach for improving the computational efficiency of reliability analysis for aeroengine turbine disc fatigue life with multiple random variables,and has great potential value for the complicated mechanical structure with multi-component and multi-failure mode.
基金Project supported by the Collaborative Research and Development Program of NSERC(Natural Sciences and Engineering Research Council of Canada) with Industrial Sponsorship from Vale,Teck Cominco,Xstrata Process Support,Agnico-Eagle,Shell Canada,Barrick Gold,COREM,SGS Lakefield Research and Flottec
文摘This work aims to provide a relationship of how the key operational variables of frother type and impeller speed affect the size of bubble （D32）. The study was performed using pilot-scale equipment （0.8 m^3） that is up to two orders of magnitude larger than equipment used for studies performed to date by others, and incorporated the key process variables of frother type and impeller speed. The results show that each frother family exhibits a unique CCC95-HLB relationship dependent on n （number of C-atoms in alkyl group） and m （number of propylene oxide group）. Empirical models were developed to predict CCC95 from HLB associated with other two parameters a and ft. The impeller speed-bubble size tests show that D32 is unaffected by increased impeller tip speed across the range of 4.6 to 9.2 m/s （representing the industrial operating range）, although D32 starts to increase below 4.6 m/s. The finding is valid for both coalescing and non-coalescing conditions. The results suggest that the bubble size and bubble size distribution （BSD） being created do not change with increasing impeller speed in the quiescent zone of the flotation.
基金supported by the National Natural Science Foundation of China (61201282)
文摘Intercepted signal blind separation is a research topic with high importance for both military and civilian communication systems. A blind separation method for space-time block code （STBC） systems is proposed by using the ordinary independent component analysis （ICA）. This method cannot work when specific complex modulations are employed since the assumption of mutual independence cannot be satisfied. The analysis shows that source signals, which are group-wise independent and use multi-dimensional ICA （MICA） instead of ordinary ICA, can be applied in this case. Utilizing the block-diagonal structure of the cumulant matrices, the JADE algorithm is generalized to the multidimensional case to separate the received data into mutually independent groups. Compared with ordinary ICA algorithms, the proposed method does not introduce additional ambiguities. Simulations show that the proposed method overcomes the drawback and achieves a better performance without utilizing coding information than channel estimation based algorithms.
文摘A new algorithm using orthogonal polynomials and sample moments was presented for estimating probability curves directly from experimental or field data of rock variables. The moments estimated directly from a sample of observed values of a random variable could be conventional moments (moments about the origin or central moments) and probability-weighted moments (PWMs). Probability curves derived from orthogonal polynomials and conventional moments are probability density functions (PDF), and probability curves derived from orthogonal polynomials and PWMs are inverse cumulative density functions (CDF) of random variables. The proposed approach is verified by two most commonly-used theoretical standard distributions: normal and exponential distribution. Examples from observed data of uniaxial compressive strength of a rock and concrete strength data are presented for illustrative purposes. The results show that probability curves of rock variable can be accurately derived from orthogonal polynomials and sample moments. Orthogonal polynomials and PWMs enable more secure inferences to be made from relatively small samples about an underlying probability curve.
基金supported by the National Natural Science Foundation of China(U14352186140340161273189)
文摘In the field of weapon system of systems (WSOS) simulation, various indicators are widely used to describe the capability of WSOS, but it is always difficult to describe the comprehensive capability of WSOS quickly and intuitively by visualization of multi-dimensional indicators. A method of machine learning and visualization is proposed, which can display and analyze the capabilities of different WSOS in a two-dimensional plane. The analysis and comparison of the comprehensive capability of different components of WSOS is realized by the method, which consists of six parts: multiple simulations, key indicators mining, three spatial distance calculation, fusion project calculation, calculation of individual capability density, and calculation of multiple capability ranges overlay. Binding a simulation experiment, the collaborative analysis of six indicators and 100 possible kinds of red WSOS are achieved. The experimental results show that this method can effectively improve the quality and speed of capabilities analysis, reveal a large number of potential information, and provide a visual support for the qualitative and quantitative analysis model.
基金This work was supported by the Natural Science Foundation of Liaoning Province(2013020022).
文摘A method is proposed to deal with the uncertain multiple attribute group decision making problems,where 2-dimension uncertain linguistic variables(2DULVs)are used as the reliable way for the experts to express their fuzzy subjective evaluation information.Firstly,in order to measure the 2DULVs more accurately,a new method is proposed to compare two 2DULVs,called a score function,while a new function is defined to measure the distance between two 2DULVs.Secondly,two optimization models are established to determine the weight of experts and attributes based on the new distance formula and a weighted average operator is used to determine the comprehensive evaluation value of each alternative.Then,a score function is used to determine the ranking of the alternatives.Finally,the effectiveness of the proposed method is proved by an illustrated example.
基金Project(2007CB714407) supported by the Major State Basic Research and Development Program of ChinaProject(2004DFA06300) supported by Key International Collaboration Project in Science and TechnologyProjects(40571107, 40701102) supported by the National Natural Science Foundation of China
文摘In order to improve the accuracy of biophysical parameters retrieved from remotely sensing data, a new algorithm was presented by using spatial contextual to estimate canopy variables from high-resolution remote sensing images. The developed algorithm was used for inversion of leaf area index (LAI) from Enhanced Thematic Mapper Plus (ETM+) data by combining with optimization method to minimize cost functions. The results show that the distribution of LAI is spatially consistent with the false composition imagery from ETM+ and the accuracy of LAI is significantly improved over the results retrieved by the conventional pixelwise retrieval methods, demonstrating that this method can be reliably used to integrate spatial contextual information for inverting LAI from high-resolution remote sensing images.
基金This work was supported by the Natural Science Foundation of Hebei Province(F2019203505).
文摘Input variables selection(IVS) is proved to be pivotal in nonlinear dynamic system modeling. In order to optimize the model of the nonlinear dynamic system, a fuzzy modeling method for determining the premise structure by selecting important inputs of the system is studied. Firstly, a simplified two stage fuzzy curves method is proposed, which is employed to sort all possible inputs by their relevance with outputs, select the important input variables of the system and identify the structure.Secondly, in order to reduce the complexity of the model, the standard fuzzy c-means clustering algorithm and the recursive least squares algorithm are used to identify the premise parameters and conclusion parameters, respectively. Then, the effectiveness of IVS is verified by two well-known issues. Finally, the proposed identification method is applied to a realistic variable load pneumatic system. The simulation experiments indi cate that the IVS method in this paper has a positive influence on the approximation performance of the Takagi-Sugeno(T-S) fuzzy modeling.
文摘Aiming at the phenomenon of discrete variables whic h generally exists in engineering structural optimization, a novel hybrid genetic algorithm (HGA) is proposed to directly search the optimal solution in this pape r. The imitative full-stress design method (IFS) was presented for discrete struct ural optimum design subjected to multi-constraints. To reach the imitative full -stress state for dangerous members was the target of IFS through iteration. IF S is integrated in the GA. The basic idea of HGA is to divide the optimization t ask into two complementary parts. The coarse, global optimization is done by the GA while local refinement is done by IFS. For instance, every K generations, th e population is doped with a locally optimal individual obtained from IFS. Both methods run in parallel. All or some of individuals are continuously used as initial values for IFS. The locally optimized individuals are re-implanted into the current generation in the GA. From some numeral examples, hybridizatio n has been discovered as enormous potential for improvement of genetic algorit hm. Selection is the component which guides the HGA to the solution by preferring in dividuals with high fitness over low-fitted ones. Selection can be deterministi c operation, but in most implementations it has random components. "Elite surviv al" is introduced to avoid that the observed best-fitted individual dies out, j ust by selecting it for the next generation without any random experiments. The individuals of population are competitive only in the same generation. There exists no competition among different generations. So HGA may be permitted to h ave different evaluation criteria for different generations. Multi-Selectio n schemes are adopted to avoid slow refinement since the individuals have si milar fitness values in the end phase of HGA. The feasibility of this method is tested with examples of engineering design wit h discrete variables. Results demonstrate the validity of HGA.
基金supported by the National Key Research and Development Program of China(2016YFE0200400)the Key R&D Program of Shaanxi Province(2017KW-ZD-12)+1 种基金the Postdoctoral Science Foundation of Shaanxi Provincethe Nature Science Foundation of Shaanxi Province
文摘Space-time coding radar has been recently proposed and investigated.It is a radar framework which can perform transmit beamforming at the receiver.However,the range resolution decreases when the number of the transmit element increases.A subarray-based space-time coding(sub-STC)radar is explored to alleviate the range resolution reduction.For the proposed radar configuration,an identical waveform is transmitted and it introduces a small time offset in different subarrays.The multidimensional ambiguity function of sub-STC radar is defined by considering resolutions in multiple domains including the range,Doppler,angle and probing direction.Analyses on properties of the multi-dimensional ambiguity function of the sub-STC radar with regard to the spatial coverage,resolution performance and low sidelobes are also given.Results reveal that the range resolution and low sidelobes performance are improved with the proposed approach.
