This paper focuses on the parameter identification problem for Wiener nonlinear dynamic systems with moving average noises. In order to improve the convergence rate, the gradient-based iterative algorithm is presented...
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This paper focuses on the parameter identification problem for Wiener nonlinear dynamic systems with moving average noises. In order to improve the convergence rate, the gradient-based iterative algorithm is presented by replacing the unmeasurable variables with their corresponding iterative estimates, and to compute iteratively the noise estimates based on the obtained parameter estimates. The simulation results show that the proposed algorithm can effectively estimate the parameters of Wiener systems with moving average noises.
By applying the auxiliary variational principle technique, the existence of solutions for a new class of generalized mixed implicit quasi-variational-like inequalities and the convergence criteria of a new iterative a...
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By applying the auxiliary variational principle technique, the existence of solutions for a new class of generalized mixed implicit quasi-variational-like inequalities and the convergence criteria of a new iterative algorithm to compute approximate solutions are proved in Hilbert spaces. The obtained result is a improvement over and generalization of the main theorem proposed by Ding.
Under the condition of uniaxial rotation test and using norm restriction of the angular rotation vector, a nonlinear equations set including 6 uncorrelated rotations is established to define the SIMU calibration frame...
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ISBN:
(纸本)9781479900305
Under the condition of uniaxial rotation test and using norm restriction of the angular rotation vector, a nonlinear equations set including 6 uncorrelated rotations is established to define the SIMU calibration frame. A test scheme of clockwise & counter clockwise rotations is adopted to eliminate the effect of earth rotation and gyro drift errors. Linearization and iterative algorithm are put forward to resolve the nonlinear equations set with very high precision. In accelerometer calibration model, the two-order nonlinear coefficient and cross-coupling coefficient are both considered. The static multi-position method is used to calibrate accelerometers, but in each static position, it is necessary to conduct an extra vertical rotation test to determine gravitation vector in SIMU frame and the result can be used as accelerometer input reference. A static nine-position accelerometer calibration scheme is presented and the simulation results show that scale factor matrix and bias can be estimated with high accuracy, but the two-order nonlinear coefficient and cross-coupling coefficient are relatively affected by accelerometer measurement noise.
The 7R 6-degree-of-freedom robots with hollow non-spherical wrist have been proven more suitable to spray painting. However, the inverse kinematics of this robot is still imperfect due to the coupling between position...
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The 7R 6-degree-of-freedom robots with hollow non-spherical wrist have been proven more suitable to spray painting. However, the inverse kinematics of this robot is still imperfect due to the coupling between position and orientation of the end-effector. In this article, a reliable numerical iterative algorithm for the inverse kinematics of a 7R 6-degree-of-freedom robot is proposed. Based on the geometry of the robot, the inverse kinematics is converted into a one-dimensional iterative research problem. Since the Jacobian matrix is not utilized, the proposed algorithm possesses good convergence, even for singular configurations. Moreover, the multiple-solution problem in the inverse kinematics is also discussed. By introducing three robot configuration indicators which are prespecified by a user, the correct solution could be chosen from all the possible solutions. In order to verify the accuracy and efficiency of the proposed algorithm, several simulations are implemented on a practical 7R 6-degree-of-freedom painting robot. The result shows that the proposed algorithm is more advantageous for a continuous trajectory.
As the explosive growth of wireless date requirements, heterogeneous network(HetN et) has become an effective solution for improving the system performance such as the throughput. The femtocells are always arranged to...
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As the explosive growth of wireless date requirements, heterogeneous network(HetN et) has become an effective solution for improving the system performance such as the throughput. The femtocells are always arranged to share the spectrum with the macro base stations(MBSs). Thus, the cochannel interference leads to the degradation of the HetN et throughput. In this paper, we discuss the program of spectrum reuse in the two-tier Het Net, and the problem is defined as a Stackelberg game approach. The MBS is play as a leader and it releases a part of spectrum resource for femtocells to avoid intertier interference. And the femtocells provide services to fractional macro users(MUEs) in return. Therefore, the throughput can be improved by the reduction of the inter-tier interference. Compared with the former works, the prominent characteristic of the method in the paper is that the benefit relation between the leader and followers is not measured by the real money. Furthermore, considering the system throughput specifically, we define the utility of the femto base stations(FBSs) by the average throughput as same as the utility of the MBS, which is used to improve the overall throughput of the system. Moreover, the gradient descent algorithm is also applied to compute the Nash equilibrium as the range of variables become continuous. The simulation results indicate that the proposed algorithm can observably reduce the interference and enhance the throughput of the network.
To solve the schema deception and premature convergence problem in the pure genetic algorithm, based on the theory method of interval, Banach fixpoint and genetic algorithms, the contractive-mapping-hybrid-genetic alg...
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To solve the schema deception and premature convergence problem in the pure genetic algorithm, based on the theory method of interval, Banach fixpoint and genetic algorithms, the contractive-mapping-hybrid-genetic algorithms (CMGA) were constructed and quadratic extension of Lipschitz was applied to testify the multi mode function extremum. The calculating examples validated the algorithmpsilas excellent performance in the global optimization problem The verifying terms are simple and easy to be actualized. The algorithms speed up the convergence obviously and improved reliability, thus the schema deception and premature convergence problem can be well solved.
This paper concentrates on the target localization problem in a distributed multiple-input multiple-output radar system using the bistatic range (BR) measurements. By linearizing the BR measurements and considering th...
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This paper concentrates on the target localization problem in a distributed multiple-input multiple-output radar system using the bistatic range (BR) measurements. By linearizing the BR measurements and considering the relationship between the nuisance parameter and the target position, a constrained weighted least squares (CWLS) problem is formulated, which is an indefinite quadratically constrained quadratic programming problem. Since the constraint is non-convex, it is a nontrivial task to find the global solution. For this purpose, an improved Newton's method is applied to the CWLS problem to estimate the target position. Numerical simulations are included to examine the algorithm's performance and corroborate the theoretical developments.
In this paper, an iterative soft multiuser detection (MUD) algorithm is proposed for multiple-input multiple-output multi-carrier code-division multiple access (MIMO MC-CDMA) systems. Based on an equivalent system mod...
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In this paper, an iterative soft multiuser detection (MUD) algorithm is proposed for multiple-input multiple-output multi-carrier code-division multiple access (MIMO MC-CDMA) systems. Based on an equivalent system model, an efficient soft MUD algorithm is first derived by the central limit theorem, the property of the complex Gaussian distribution, and fast matrix computation formulas. By iteratively using the soft MUD algorithm with some updated probability information, we then obtain the proposed iterative soft MUD algorithm. Finally, it is shown that this algorithm achieves near-optimal performance with very efficient iterative computations.
In this paper, we use the Yamada's method to modify the normal Mann's iterative process to have strong convergence for a k-strictly pseudo-contractive mapping in the framework of Hilbert spaces.
In this paper, we use the Yamada's method to modify the normal Mann's iterative process to have strong convergence for a k-strictly pseudo-contractive mapping in the framework of Hilbert spaces.
This paper proposes an algorithm that solves planar homography by iterative linear optimization. We iteratively employ direct linear transformation (DLT) algorithm to robustly estimate the homography induced by a give...
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This paper proposes an algorithm that solves planar homography by iterative linear optimization. We iteratively employ direct linear transformation (DLT) algorithm to robustly estimate the homography induced by a given set of point correspondences under perspective transformation. By simple on-the-fly homogeneous coordinate adjustment we progressively minimize the difference between the algebraic error and the geometric error. When the difference is sufficiently close to zero, the geometric error is equivalently minimized and the homography is reliably solved. Backward covariance propagation is employed to do error analysis. The experiments prove that the algorithm is able to find global minimum despite erroneous initialization. It gives very precise estimate at low computational cost and greatly outperforms existing techniques.
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