Dynamic model of aerial towed decoy system is established and simulations are performed to research the dynamic characteristics of the system. Firstly, Kinetic equations based on spinor are built, where the cable is d...Dynamic model of aerial towed decoy system is established and simulations are performed to research the dynamic characteristics of the system. Firstly, Kinetic equations based on spinor are built, where the cable is discretized into a number of rigid segments while the decoy is modeled as a rigid body hinged on the cable. Then tension recurrence algorithm is developed to improve computational efficiency, which makes it possible to predict the dynamic response of aerial towed decoy system rapidly and accurately. Subsequently, the efficiency and validity of this algorithm are verified by comparison with Kane’s function and further validated by wind tunnel tests.Simulation results indicate that the distance between the towing point and the decoy’s center of gravity is suggested to be 5%–20% of the length of decoy body to ensure the stability of system.In up-risen maneuver process, the value of angular velocity is recommended to be less than0.10 rad/s to protect the cable from the aircraft exhaust jet. During the turning movement of aircraft, the cable’s extent of stretching outwards is proportional to the aircraft’s angular velocity.Meanwhile, the decoy, aircraft and missile form a triangle, which promotes the decoy’s performance.展开更多
In this paper, a practical Werner-type continued fraction method for solving matrix valued rational interpolation problem is provided by using a generalized inverse of matrices. In order to reduce the continued fracti...In this paper, a practical Werner-type continued fraction method for solving matrix valued rational interpolation problem is provided by using a generalized inverse of matrices. In order to reduce the continued fraction form to rational function form of the interpolants, an efficient forward recurrence algorithm is obtained.展开更多
A new column recurrence algorithm based on the classical Greville method and modified Huang update is proposed for computing generalized inverse matrix and least squares solution. The numerical results have shown the ...A new column recurrence algorithm based on the classical Greville method and modified Huang update is proposed for computing generalized inverse matrix and least squares solution. The numerical results have shown the high efficiency and stability of the algorithm.展开更多
This paper presents an algorithm for computing a linear recurrence system R(n,m)of order m for n equations on MIMD parallel system.This algorithm is not only easy to be programmed on a parallel computer system,but als...This paper presents an algorithm for computing a linear recurrence system R(n,m)of order m for n equations on MIMD parallel system.This algorithm is not only easy to be programmed on a parallel computer system,but also reduces the data-waiting time due to compute-ahead strategy.The paper analyses how to achieve maximal load balancing when the algorithm is implemented on MIMD parallel system.By the end of the paper,an analysis on the speedup and parallel efficiency are given.The results indicate that the new parallel elimination algorithm has great improvement compared with the old ones.展开更多
In this paper a novel class of neural networks called generalized congruence neural networks (GCNN) is proposed. All neurons in the neural networks are activated in the form of congruence. The architectures, learnin...In this paper a novel class of neural networks called generalized congruence neural networks (GCNN) is proposed. All neurons in the neural networks are activated in the form of congruence. The architectures, learning rules and two algorithms are presented. Simulation results indicate that such network has satisfactory generalization properties near the sample points. Since this kind of neural nets can be easily operated and implemented, it is appropriate to make further research concerning the theory and applications of GCNN.展开更多
A DRNN (diagonal recurrent neural network) and its RPE (recurrent prediction error) learning algorithm are proposed in this paper .Using of the simple structure of DRNN can reduce the capacity of calculation. The prin...A DRNN (diagonal recurrent neural network) and its RPE (recurrent prediction error) learning algorithm are proposed in this paper .Using of the simple structure of DRNN can reduce the capacity of calculation. The principle of RPE learning algorithm is to adjust weights along the direction of Gauss-Newton. Meanwhile, it is unnecessary to calculate the second local derivative and the inverse matrixes, whose unbiasedness is proved. With application to the extremely short time prediction of large ship pitch, satisfactory results are obtained. Prediction effect of this algorithm is compared with that of auto-regression and periodical diagram method, and comparison results show that the proposed algorithm is feasible.展开更多
文摘Dynamic model of aerial towed decoy system is established and simulations are performed to research the dynamic characteristics of the system. Firstly, Kinetic equations based on spinor are built, where the cable is discretized into a number of rigid segments while the decoy is modeled as a rigid body hinged on the cable. Then tension recurrence algorithm is developed to improve computational efficiency, which makes it possible to predict the dynamic response of aerial towed decoy system rapidly and accurately. Subsequently, the efficiency and validity of this algorithm are verified by comparison with Kane’s function and further validated by wind tunnel tests.Simulation results indicate that the distance between the towing point and the decoy’s center of gravity is suggested to be 5%–20% of the length of decoy body to ensure the stability of system.In up-risen maneuver process, the value of angular velocity is recommended to be less than0.10 rad/s to protect the cable from the aircraft exhaust jet. During the turning movement of aircraft, the cable’s extent of stretching outwards is proportional to the aircraft’s angular velocity.Meanwhile, the decoy, aircraft and missile form a triangle, which promotes the decoy’s performance.
文摘In this paper, a practical Werner-type continued fraction method for solving matrix valued rational interpolation problem is provided by using a generalized inverse of matrices. In order to reduce the continued fraction form to rational function form of the interpolants, an efficient forward recurrence algorithm is obtained.
文摘A new column recurrence algorithm based on the classical Greville method and modified Huang update is proposed for computing generalized inverse matrix and least squares solution. The numerical results have shown the high efficiency and stability of the algorithm.
文摘This paper presents an algorithm for computing a linear recurrence system R(n,m)of order m for n equations on MIMD parallel system.This algorithm is not only easy to be programmed on a parallel computer system,but also reduces the data-waiting time due to compute-ahead strategy.The paper analyses how to achieve maximal load balancing when the algorithm is implemented on MIMD parallel system.By the end of the paper,an analysis on the speedup and parallel efficiency are given.The results indicate that the new parallel elimination algorithm has great improvement compared with the old ones.
文摘In this paper a novel class of neural networks called generalized congruence neural networks (GCNN) is proposed. All neurons in the neural networks are activated in the form of congruence. The architectures, learning rules and two algorithms are presented. Simulation results indicate that such network has satisfactory generalization properties near the sample points. Since this kind of neural nets can be easily operated and implemented, it is appropriate to make further research concerning the theory and applications of GCNN.
文摘A DRNN (diagonal recurrent neural network) and its RPE (recurrent prediction error) learning algorithm are proposed in this paper .Using of the simple structure of DRNN can reduce the capacity of calculation. The principle of RPE learning algorithm is to adjust weights along the direction of Gauss-Newton. Meanwhile, it is unnecessary to calculate the second local derivative and the inverse matrixes, whose unbiasedness is proved. With application to the extremely short time prediction of large ship pitch, satisfactory results are obtained. Prediction effect of this algorithm is compared with that of auto-regression and periodical diagram method, and comparison results show that the proposed algorithm is feasible.
