A new iterative method,which is called positive interior-point algorithm,is presented for solving the nonlinear complementarity problems.This method is of the desirable feature of robustness.And the convergence theore...A new iterative method,which is called positive interior-point algorithm,is presented for solving the nonlinear complementarity problems.This method is of the desirable feature of robustness.And the convergence theorems of the algorithm is established.In addition,some numerical results are reported.展开更多
In this paper,we study the nonlinear matrix equation X-A^(H)X^(-1)A=Q,where A,Q∈C^(n×n),Q is a Hermitian positive definite matrix and X∈C^(n×n)is an unknown matrix.We prove that the equation always has a u...In this paper,we study the nonlinear matrix equation X-A^(H)X^(-1)A=Q,where A,Q∈C^(n×n),Q is a Hermitian positive definite matrix and X∈C^(n×n)is an unknown matrix.We prove that the equation always has a unique Hermitian positive definite solution.We present two structure-preserving-doubling like algorithms to find the Hermitian positive definite solution of the equation,and the convergence theories are established.Finally,we show the effectiveness of the algorithms by numerical experiments.展开更多
In this paper,we propose a new full-Newton step feasible interior-point algorithm for the special weighted linear complementarity problems.The proposed algorithm employs the technique of algebraic equivalent transform...In this paper,we propose a new full-Newton step feasible interior-point algorithm for the special weighted linear complementarity problems.The proposed algorithm employs the technique of algebraic equivalent transformation to derive the search direction.It is shown that the proximity measure reduces quadratically at each iteration.Moreover,the iteration bound of the algorithm is as good as the best-known polynomial complexity for these types of problems.Furthermore,numerical results are presented to show the efficiency of the proposed algorithm.展开更多
To guarantee the optimal reduct set, a heuristic reduction algorithm is proposed, which considers the distinguishing information between the members of each pair decision classes. Firstly the pairwise positive region ...To guarantee the optimal reduct set, a heuristic reduction algorithm is proposed, which considers the distinguishing information between the members of each pair decision classes. Firstly the pairwise positive region is defined, based on which the pairwise significance measure is calculated between the members of each pair classes. Finally the weighted pairwise significance of attribute is used as the attribute reduction criterion, which indicates the necessity of attributes very well. By introducing the noise tolerance factor, the new algorithm can tolerate noise to some extent. Experimental results show the advantages of our novel heuristic reduction algorithm over the traditional attribute dependency based algorithm.展开更多
This article presents a polynomial predictor-corrector interior-point algorithm for convex quadratic programming based on a modified predictor-corrector interior-point algorithm. In this algorithm, there is only one c...This article presents a polynomial predictor-corrector interior-point algorithm for convex quadratic programming based on a modified predictor-corrector interior-point algorithm. In this algorithm, there is only one corrector step after each predictor step, where Step 2 is a predictor step and Step 4 is a corrector step in the algorithm. In the algorithm, the predictor step decreases the dual gap as much as possible in a wider neighborhood of the central path and the corrector step draws iteration points back to a narrower neighborhood and make a reduction for the dual gap. It is shown that the algorithm has O（√nL） iteration complexity which is the best result for convex quadratic programming so far.展开更多
The existing active tag-based radio frequency identi-fication(RFID)localization techniques show low accuracy in practical applications.To address such problems,we propose a chaotic adaptive genetic algorithm to align ...The existing active tag-based radio frequency identi-fication(RFID)localization techniques show low accuracy in practical applications.To address such problems,we propose a chaotic adaptive genetic algorithm to align the passive tag ar-rays.We use chaotic sequences to generate the intersection points,the weakest single point intersection is used to ensure the convergence accuracy of the algorithm while avoiding the optimization jitter problem.Meanwhile,to avoid the problem of slow convergence and immature convergence of the algorithm caused by the weakening of individual competition at a later stage,we use adaptive rate of change to improve the optimiza-tion efficiency.In addition,to remove signal noise and outliers,we preprocess the data using Gaussian filtering.Experimental results demonstrate that the proposed algorithm achieves high-er localization accuracy and improves the convergence speed.展开更多
Interior-point methods （IPMs） for linear optimization （LO） and semidefinite optimization （SDO） have become a hot area in mathematical programming in the last decades. In this paper, a new kernel function with si...Interior-point methods （IPMs） for linear optimization （LO） and semidefinite optimization （SDO） have become a hot area in mathematical programming in the last decades. In this paper, a new kernel function with simple algebraic expression is proposed. Based on this kernel function, a primal-dual interior-point methods （IPMs） for semidefinite optimization （SDO） is designed. And the iteration complexity of the algorithm as O（n^3/4 log n/ε） with large-updates is established. The resulting bound is better than the classical kernel function, with its iteration complexity O（n log n/ε） in large-updates case.展开更多
In this paper, primal-dual interior-point algorithm with dynamic step size is implemented for linear programming （LP） problems. The algorithms are based on a few kernel functions, including both serf-regular functio...In this paper, primal-dual interior-point algorithm with dynamic step size is implemented for linear programming （LP） problems. The algorithms are based on a few kernel functions, including both serf-regular functions and non-serf-regular ones. The dynamic step size is compared with fixed step size for the algorithms in inner iteration of Newton step. Numerical tests show that the algorithms with dynaraic step size are more efficient than those with fixed step size.展开更多
In this paper, we propose an arc-search interior-point algorithm for convex quadratic programming with a wide neighborhood of the central path, which searches the optimizers along the ellipses that approximate the ent...In this paper, we propose an arc-search interior-point algorithm for convex quadratic programming with a wide neighborhood of the central path, which searches the optimizers along the ellipses that approximate the entire central path. The favorable polynomial complexity bound of the algorithm is obtained, namely O（nlog（（ x^0）~TS^0/ε）） which is as good as the linear programming analogue. Finally, the numerical experiments show that the proposed algorithm is efficient.展开更多
Because of the ignored items after linearization,the extended Kalman filter(EKF)becomes a form of suboptimal gradient descent algorithm.The emanative tendency exists in GPS solution when the filter equations are ill-p...Because of the ignored items after linearization,the extended Kalman filter(EKF)becomes a form of suboptimal gradient descent algorithm.The emanative tendency exists in GPS solution when the filter equations are ill-posed.The deviation in the estimation cannot be avoided.Furthermore,the true solution may be lost in pseudorange positioning because the linearized pseudorange equations are partial solutions.To solve the above problems in GPS dynamic positioning by using EKF,a closed-form Kalman filter method called the two-stage algorithm is presented for the nonlinear algebraic solution of GPS dynamic positioning based on the global nonlinear least squares closed algorithm--Bancroft numerical algorithm of American.The method separates the spatial parts from temporal parts during processing the GPS filter problems,and solves the nonlinear GPS dynamic positioning,thus getting stable and reliable dynamic positioning solutions.展开更多
In this paper, we design a primal-dual interior-point algorithm for linear optimization. Search directions and proximity function are proposed based on a new kernel function which includes neither growth term nor barr...In this paper, we design a primal-dual interior-point algorithm for linear optimization. Search directions and proximity function are proposed based on a new kernel function which includes neither growth term nor barrier term. Iteration bounds both for large-and small-update methods are derived, namely, O（nlog（n/c）） and O（√nlog（n/ε））. This new kernel function has simple algebraic expression and the proximity function has not been used before. Analogous to the classical logarithmic kernel function, our complexity analysis is easier than the other pri- mal-dual interior-point methods based on logarithmic barrier functions and recent kernel functions.展开更多
In this paper,a new full-Newton step primal-dual interior-point algorithm for solving the special weighted linear complementarity problem is designed and analyzed.The algorithm employs a kernel function with a linear ...In this paper,a new full-Newton step primal-dual interior-point algorithm for solving the special weighted linear complementarity problem is designed and analyzed.The algorithm employs a kernel function with a linear growth term to derive the search direction,and by introducing new technical results and selecting suitable parameters,we prove that the iteration bound of the algorithm is as good as best-known polynomial complexity of interior-point methods.Furthermore,numerical results illustrate the efficiency of the proposed method.展开更多
Global navigation satellite system could provide accurate positioning results in signal complete condition. However, the performance is severe when signal denied, especially for the single-mode Bei Dou receiver. This ...Global navigation satellite system could provide accurate positioning results in signal complete condition. However, the performance is severe when signal denied, especially for the single-mode Bei Dou receiver. This paper proposes a dual-satellite positioning algorithm to promote the positioning performance in the satellite signal gap. The new algorithm utilizes the previous positioning data stored in complete condition to simplify the positioning equations. As the clock bias persists for a short period, this proposed method could work out accurate positioning results by only two visible satellites, without the need of computing the clock bias. Also, the Kalman filtering algorithm is used to smooth the trajectories, and improve the positioning results. During the incomplete period, only two satellites for 30 seconds and three satellites for 60 seconds, the preliminary experiment result shows that, the presented method could provide almost the same positioning results as in complete condition.展开更多
In this paper, a primal-dual path-following interior-point algorithm for linearly constrained convex optimization(LCCO) is presented.The algorithm is based on a new technique for finding a class of search directions a...In this paper, a primal-dual path-following interior-point algorithm for linearly constrained convex optimization(LCCO) is presented.The algorithm is based on a new technique for finding a class of search directions and the strategy of the central path.At each iteration, only full-Newton steps are used.Finally, the favorable polynomial complexity bound for the algorithm with the small-update method is deserved, namely, O(√n log n /ε).展开更多
The mobility of the targets asks for high requirements of the locating speed in indoor positioning systems.The standard medium access control(MAC)algorithm will often cause lots of packet conflicts and high transmissi...The mobility of the targets asks for high requirements of the locating speed in indoor positioning systems.The standard medium access control(MAC)algorithm will often cause lots of packet conflicts and high transmission delay if multiple users communicate with one beacon at the same time,which will severely limit the speed of the system.Therefore,an optimized MAC algorithm is proposed based on channel reservation to enable users to reserve beacons.A frame threshold is set to ensure the users with shorter data frames do not depend on the reservation mechanism,and multiple users can achieve packets switching with relative beacon in a fixed sequence by using frequency division multiplexing technology.The simulation results show that the optimized MAC algorithm proposed in this paper can improve the positioning speed significantly while maintaining the positioning accuracy.Moreover,the positioning accuracy can be increased to a certain extent if more channel resources can be obtained,so as to provide effective technical support for the location and tracking applications of indoor moving targets.展开更多
The theoretical positioning accuracy of multilateration(MLAT) with the time difference of arrival(TDOA) algorithm is very high. However, there are some problems in practical applications. Here we analyze the location ...The theoretical positioning accuracy of multilateration(MLAT) with the time difference of arrival(TDOA) algorithm is very high. However, there are some problems in practical applications. Here we analyze the location performance of the time sum of arrival(TSOA) algorithm from the root mean square error(RMSE) and geometric dilution of precision(GDOP) in additive white Gaussian noise(AWGN) environment. The TSOA localization model is constructed. Using it, the distribution of location ambiguity region is presented with 4-base stations. And then, the location performance analysis is started from the 4-base stations with calculating the RMSE and GDOP variation. Subsequently, when the location parameters are changed in number of base stations, base station layout and so on, the performance changing patterns of the TSOA location algorithm are shown. So, the TSOA location characteristics and performance are revealed. From the RMSE and GDOP state changing trend, the anti-noise performance and robustness of the TSOA localization algorithm are proved. The TSOA anti-noise performance will be used for reducing the blind-zone and the false location rate of MLAT systems.展开更多
This note deals with how to position bricks so that m aximizing the numbers of whole brick in a given area. A method by genetic algori thm is given to solve this problem. By this method, the numbers of whole brick a n...This note deals with how to position bricks so that m aximizing the numbers of whole brick in a given area. A method by genetic algori thm is given to solve this problem. By this method, the numbers of whole brick a nd their position are gained when given areas are convex polygon and brick is re ctangular, and you can easily design a CAD soft to optimize the scheme of positi oning bricks. It is huge advantage by this method when given areas are nonregula r. Some rules of parameter’s influence to algorithm are pointed out by computer simulation. The first section states the problem and the math model of problem is given out. The second section gives out the solution by genetic algorithm, in cluding description of genetic algorithm and steps of algorithm about proble m of positioning bricks. The third section gives a computer simulation example. The last section is some discussions about this algorithm, including the influen ce of parameter to algorithm and optimizing parameter. Some rule is gained.展开更多
As increase of disk access speed has far lagged the speed of processors and main memory, disk-scheduling performance, although less significant for personal users with dedicated storage, is crucial for internet-based ...As increase of disk access speed has far lagged the speed of processors and main memory, disk-scheduling performance, although less significant for personal users with dedicated storage, is crucial for internet-based intensive data processing. For modern disks, increase of disk rotation rate makes overhead of disk access to data transfer heavier. Therefore, it seems more important to improve both parallel processing capability of disk I/O and disk-scheduling performance at the same time. For disk-scheduling algorithms based on both disk arm and rotational positions, their time-resolving powers are more precise in comparison with those for disk-scheduling algorithms based only on disk arm position. Algorithms of this sort are studied in this paper. Several improved algorithms based on rotational position are proposed, and simulation results of their performances demonstrate.展开更多
This paper presents a new distributed positioning algorithm for unknown nodes in a wireless sensor network. The algorithm is based exclusively on connectivity. First, assuming that the positions of the anchor nodes ar...This paper presents a new distributed positioning algorithm for unknown nodes in a wireless sensor network. The algorithm is based exclusively on connectivity. First, assuming that the positions of the anchor nodes are already known, a circular belt containing an unknown node is obtained using information about the anchor nodes that are in radio range of the unknown node, based on the geometric relationships and communication constraints among the unknown node and the anchor nodes. Then, the centroid of the circular belt is taken to be the estimated position of the unknown node. Since the algorithm is very simple and since the only communication needed is between the anchor nodes and the unknown node, the communication and computational loads are very small. Furthermore, the algorithm is robust because neither the failure of old unknown nodes nor the addition of new unknown nodes influences the positioning of unknown nodes to be located. A theoretical analysis and simulation results show that the algorithm does not produce any cumulative error and is insensitive to range error, and that a change in the number of sensor nodes does not affect the communication or computational load. These features make this algorithm suitable for all sizes of low-power wireless sensor networks.展开更多
The simplified Newton method, at the expense of fast convergence, reduces the work required by Newton method by reusing the initial Jacobian matrix. The composite Newton method attempts to balance the trade-off betwee...The simplified Newton method, at the expense of fast convergence, reduces the work required by Newton method by reusing the initial Jacobian matrix. The composite Newton method attempts to balance the trade-off between expense and fast convergence by composing one Newton step with one simplified Newton step. Recently, Mehrotra suggested a predictor-corrector variant of primal-dual interior point method for linear programming. It is currently the interiorpoint method of the choice for linear programming. In this work we propose a predictor-corrector interior-point algorithm for convex quadratic programming. It is proved that the algorithm is equivalent to a level-1 perturbed composite Newton method. Computations in the algorithm do not require that the initial primal and dual points be feasible. Numerical experiments are made.展开更多
文摘A new iterative method,which is called positive interior-point algorithm,is presented for solving the nonlinear complementarity problems.This method is of the desirable feature of robustness.And the convergence theorems of the algorithm is established.In addition,some numerical results are reported.
基金This research is supported by the National Natural Science Foundation of China(No.11871444).
文摘In this paper,we study the nonlinear matrix equation X-A^(H)X^(-1)A=Q,where A,Q∈C^(n×n),Q is a Hermitian positive definite matrix and X∈C^(n×n)is an unknown matrix.We prove that the equation always has a unique Hermitian positive definite solution.We present two structure-preserving-doubling like algorithms to find the Hermitian positive definite solution of the equation,and the convergence theories are established.Finally,we show the effectiveness of the algorithms by numerical experiments.
基金Supported by the Optimisation Theory and Algorithm Research Team(Grant No.23kytdzd004)University Science Research Project of Anhui Province(Grant No.2024AH050631)the General Programs for Young Teacher Cultivation of Educational Commission of Anhui Province(Grant No.YQYB2023090).
文摘In this paper,we propose a new full-Newton step feasible interior-point algorithm for the special weighted linear complementarity problems.The proposed algorithm employs the technique of algebraic equivalent transformation to derive the search direction.It is shown that the proximity measure reduces quadratically at each iteration.Moreover,the iteration bound of the algorithm is as good as the best-known polynomial complexity for these types of problems.Furthermore,numerical results are presented to show the efficiency of the proposed algorithm.
基金Sponsored by the Ministerial Level Advanced Research Foundation(11415133)
文摘To guarantee the optimal reduct set, a heuristic reduction algorithm is proposed, which considers the distinguishing information between the members of each pair decision classes. Firstly the pairwise positive region is defined, based on which the pairwise significance measure is calculated between the members of each pair classes. Finally the weighted pairwise significance of attribute is used as the attribute reduction criterion, which indicates the necessity of attributes very well. By introducing the noise tolerance factor, the new algorithm can tolerate noise to some extent. Experimental results show the advantages of our novel heuristic reduction algorithm over the traditional attribute dependency based algorithm.
基金Project supported by the National Science Foundation of China (60574071) the Foundation for University Key Teacher by the Ministry of Education.
文摘This article presents a polynomial predictor-corrector interior-point algorithm for convex quadratic programming based on a modified predictor-corrector interior-point algorithm. In this algorithm, there is only one corrector step after each predictor step, where Step 2 is a predictor step and Step 4 is a corrector step in the algorithm. In the algorithm, the predictor step decreases the dual gap as much as possible in a wider neighborhood of the central path and the corrector step draws iteration points back to a narrower neighborhood and make a reduction for the dual gap. It is shown that the algorithm has O（√nL） iteration complexity which is the best result for convex quadratic programming so far.
基金supported by the Aviation Science Foundation(ASFC-20181352009).
文摘The existing active tag-based radio frequency identi-fication(RFID)localization techniques show low accuracy in practical applications.To address such problems,we propose a chaotic adaptive genetic algorithm to align the passive tag ar-rays.We use chaotic sequences to generate the intersection points,the weakest single point intersection is used to ensure the convergence accuracy of the algorithm while avoiding the optimization jitter problem.Meanwhile,to avoid the problem of slow convergence and immature convergence of the algorithm caused by the weakening of individual competition at a later stage,we use adaptive rate of change to improve the optimiza-tion efficiency.In addition,to remove signal noise and outliers,we preprocess the data using Gaussian filtering.Experimental results demonstrate that the proposed algorithm achieves high-er localization accuracy and improves the convergence speed.
基金Project supported by the National Natural Science Foundation of China （Grant No. 10117733）, the Shanghai Leading Academic Discipline Project （Grant No.J50101）, and the Foundation of Scientific Research for Selecting and Cultivating Young Excellent University Teachers in Shanghai （Grant No.06XPYQ52）
文摘Interior-point methods （IPMs） for linear optimization （LO） and semidefinite optimization （SDO） have become a hot area in mathematical programming in the last decades. In this paper, a new kernel function with simple algebraic expression is proposed. Based on this kernel function, a primal-dual interior-point methods （IPMs） for semidefinite optimization （SDO） is designed. And the iteration complexity of the algorithm as O（n^3/4 log n/ε） with large-updates is established. The resulting bound is better than the classical kernel function, with its iteration complexity O（n log n/ε） in large-updates case.
基金Project supported by Dutch Organization for Scientific Research(Grant No .613 .000 .010)
文摘In this paper, primal-dual interior-point algorithm with dynamic step size is implemented for linear programming （LP） problems. The algorithms are based on a few kernel functions, including both serf-regular functions and non-serf-regular ones. The dynamic step size is compared with fixed step size for the algorithms in inner iteration of Newton step. Numerical tests show that the algorithms with dynaraic step size are more efficient than those with fixed step size.
基金Supported by the National Natural Science Foundation of China(71471102)
文摘In this paper, we propose an arc-search interior-point algorithm for convex quadratic programming with a wide neighborhood of the central path, which searches the optimizers along the ellipses that approximate the entire central path. The favorable polynomial complexity bound of the algorithm is obtained, namely O（nlog（（ x^0）~TS^0/ε）） which is as good as the linear programming analogue. Finally, the numerical experiments show that the proposed algorithm is efficient.
文摘Because of the ignored items after linearization,the extended Kalman filter(EKF)becomes a form of suboptimal gradient descent algorithm.The emanative tendency exists in GPS solution when the filter equations are ill-posed.The deviation in the estimation cannot be avoided.Furthermore,the true solution may be lost in pseudorange positioning because the linearized pseudorange equations are partial solutions.To solve the above problems in GPS dynamic positioning by using EKF,a closed-form Kalman filter method called the two-stage algorithm is presented for the nonlinear algebraic solution of GPS dynamic positioning based on the global nonlinear least squares closed algorithm--Bancroft numerical algorithm of American.The method separates the spatial parts from temporal parts during processing the GPS filter problems,and solves the nonlinear GPS dynamic positioning,thus getting stable and reliable dynamic positioning solutions.
基金Supported by the Natural Science Foundation of Hubei Province (2008CDZD47)
文摘In this paper, we design a primal-dual interior-point algorithm for linear optimization. Search directions and proximity function are proposed based on a new kernel function which includes neither growth term nor barrier term. Iteration bounds both for large-and small-update methods are derived, namely, O（nlog（n/c）） and O（√nlog（n/ε））. This new kernel function has simple algebraic expression and the proximity function has not been used before. Analogous to the classical logarithmic kernel function, our complexity analysis is easier than the other pri- mal-dual interior-point methods based on logarithmic barrier functions and recent kernel functions.
基金Supported by University Science Research Project of Anhui Province(2023AH052921)Outstanding Youth Talent Project of Anhui Province(gxyq2021254)。
文摘In this paper,a new full-Newton step primal-dual interior-point algorithm for solving the special weighted linear complementarity problem is designed and analyzed.The algorithm employs a kernel function with a linear growth term to derive the search direction,and by introducing new technical results and selecting suitable parameters,we prove that the iteration bound of the algorithm is as good as best-known polynomial complexity of interior-point methods.Furthermore,numerical results illustrate the efficiency of the proposed method.
基金partially supported by the National Natural Science Foundation of China under Grant No.61601296, 61601295, and 61671304
文摘Global navigation satellite system could provide accurate positioning results in signal complete condition. However, the performance is severe when signal denied, especially for the single-mode Bei Dou receiver. This paper proposes a dual-satellite positioning algorithm to promote the positioning performance in the satellite signal gap. The new algorithm utilizes the previous positioning data stored in complete condition to simplify the positioning equations. As the clock bias persists for a short period, this proposed method could work out accurate positioning results by only two visible satellites, without the need of computing the clock bias. Also, the Kalman filtering algorithm is used to smooth the trajectories, and improve the positioning results. During the incomplete period, only two satellites for 30 seconds and three satellites for 60 seconds, the preliminary experiment result shows that, the presented method could provide almost the same positioning results as in complete condition.
基金supported by the Shanghai Pujiang Program (Grant No.06PJ14039)the Science Foundation of Shanghai Municipal Commission of Education (Grant No.06NS031)
文摘In this paper, a primal-dual path-following interior-point algorithm for linearly constrained convex optimization(LCCO) is presented.The algorithm is based on a new technique for finding a class of search directions and the strategy of the central path.At each iteration, only full-Newton steps are used.Finally, the favorable polynomial complexity bound for the algorithm with the small-update method is deserved, namely, O(√n log n /ε).
基金Supported by the National Natural Science Foundation of China(No.61771186)Outstanding Youth Project of Heilongjiang Natural Science Foundation(No.YQ2020F012)Undergraduate University Project of Young Scientist Creative Talent of Heilongjiang Province(No.UNPYSCT-2017125)。
文摘The mobility of the targets asks for high requirements of the locating speed in indoor positioning systems.The standard medium access control(MAC)algorithm will often cause lots of packet conflicts and high transmission delay if multiple users communicate with one beacon at the same time,which will severely limit the speed of the system.Therefore,an optimized MAC algorithm is proposed based on channel reservation to enable users to reserve beacons.A frame threshold is set to ensure the users with shorter data frames do not depend on the reservation mechanism,and multiple users can achieve packets switching with relative beacon in a fixed sequence by using frequency division multiplexing technology.The simulation results show that the optimized MAC algorithm proposed in this paper can improve the positioning speed significantly while maintaining the positioning accuracy.Moreover,the positioning accuracy can be increased to a certain extent if more channel resources can be obtained,so as to provide effective technical support for the location and tracking applications of indoor moving targets.
基金supported by the Joint Civil Aviation Fund of National Natural Science Foundation of China(Nos.U1533108 and U1233112)
文摘The theoretical positioning accuracy of multilateration(MLAT) with the time difference of arrival(TDOA) algorithm is very high. However, there are some problems in practical applications. Here we analyze the location performance of the time sum of arrival(TSOA) algorithm from the root mean square error(RMSE) and geometric dilution of precision(GDOP) in additive white Gaussian noise(AWGN) environment. The TSOA localization model is constructed. Using it, the distribution of location ambiguity region is presented with 4-base stations. And then, the location performance analysis is started from the 4-base stations with calculating the RMSE and GDOP variation. Subsequently, when the location parameters are changed in number of base stations, base station layout and so on, the performance changing patterns of the TSOA location algorithm are shown. So, the TSOA location characteristics and performance are revealed. From the RMSE and GDOP state changing trend, the anti-noise performance and robustness of the TSOA localization algorithm are proved. The TSOA anti-noise performance will be used for reducing the blind-zone and the false location rate of MLAT systems.
文摘This note deals with how to position bricks so that m aximizing the numbers of whole brick in a given area. A method by genetic algori thm is given to solve this problem. By this method, the numbers of whole brick a nd their position are gained when given areas are convex polygon and brick is re ctangular, and you can easily design a CAD soft to optimize the scheme of positi oning bricks. It is huge advantage by this method when given areas are nonregula r. Some rules of parameter’s influence to algorithm are pointed out by computer simulation. The first section states the problem and the math model of problem is given out. The second section gives out the solution by genetic algorithm, in cluding description of genetic algorithm and steps of algorithm about proble m of positioning bricks. The third section gives a computer simulation example. The last section is some discussions about this algorithm, including the influen ce of parameter to algorithm and optimizing parameter. Some rule is gained.
基金Project supported by National Natural Science Foundation of Chi-na( Grant No . 60373088) , and Defense Pre-research Project ofChina(Grant No .413160502)
文摘As increase of disk access speed has far lagged the speed of processors and main memory, disk-scheduling performance, although less significant for personal users with dedicated storage, is crucial for internet-based intensive data processing. For modern disks, increase of disk rotation rate makes overhead of disk access to data transfer heavier. Therefore, it seems more important to improve both parallel processing capability of disk I/O and disk-scheduling performance at the same time. For disk-scheduling algorithms based on both disk arm and rotational positions, their time-resolving powers are more precise in comparison with those for disk-scheduling algorithms based only on disk arm position. Algorithms of this sort are studied in this paper. Several improved algorithms based on rotational position are proposed, and simulation results of their performances demonstrate.
基金This work was supported by the National Science Foundation of P.R.China(No.60425310)the Teaching and Research Award Program for Outstanding Young Teachers in Higher Education Institutions of the Ministry of Education,P.R.China (TRAPOYT).
文摘This paper presents a new distributed positioning algorithm for unknown nodes in a wireless sensor network. The algorithm is based exclusively on connectivity. First, assuming that the positions of the anchor nodes are already known, a circular belt containing an unknown node is obtained using information about the anchor nodes that are in radio range of the unknown node, based on the geometric relationships and communication constraints among the unknown node and the anchor nodes. Then, the centroid of the circular belt is taken to be the estimated position of the unknown node. Since the algorithm is very simple and since the only communication needed is between the anchor nodes and the unknown node, the communication and computational loads are very small. Furthermore, the algorithm is robust because neither the failure of old unknown nodes nor the addition of new unknown nodes influences the positioning of unknown nodes to be located. A theoretical analysis and simulation results show that the algorithm does not produce any cumulative error and is insensitive to range error, and that a change in the number of sensor nodes does not affect the communication or computational load. These features make this algorithm suitable for all sizes of low-power wireless sensor networks.
文摘The simplified Newton method, at the expense of fast convergence, reduces the work required by Newton method by reusing the initial Jacobian matrix. The composite Newton method attempts to balance the trade-off between expense and fast convergence by composing one Newton step with one simplified Newton step. Recently, Mehrotra suggested a predictor-corrector variant of primal-dual interior point method for linear programming. It is currently the interiorpoint method of the choice for linear programming. In this work we propose a predictor-corrector interior-point algorithm for convex quadratic programming. It is proved that the algorithm is equivalent to a level-1 perturbed composite Newton method. Computations in the algorithm do not require that the initial primal and dual points be feasible. Numerical experiments are made.
