A recursive and efficient method for generating binary vectors in non-increasing order of their likelihood for a set of all binary vectors is proposed. Numerical results on experiments show the effectiveness of this m...
详细信息
A recursive and efficient method for generating binary vectors in non-increasing order of their likelihood for a set of all binary vectors is proposed. Numerical results on experiments show the effectiveness of this method. Efficient decoding algorithms with simulation results are also proposed as applications of the method.
Kernel principal component analysis (kernel-PCA) is an elegant nonlinear extension of one of the most used data analysis and dimensionality reduction techniques, the principal component analysis. In this paper, we pro...
详细信息
Kernel principal component analysis (kernel-PCA) is an elegant nonlinear extension of one of the most used data analysis and dimensionality reduction techniques, the principal component analysis. In this paper, we propose an online algorithm for kernel-PCA. To this end, we examine a kernel-based version of Oja's rule, initially put forward to extract a linear principal axe. As with most kernel-based machines, the model order equals the number of available observations. To provide an online scheme, we propose to control the model order. We discuss theoretical results, such as an upper bound on the error of approximating the principal functions with the reduced-order model. We derive a recursive algorithm to discover the first principal axis, and extend it to multiple axes. Experimental results demonstrate the effectiveness of the proposed approach, both on synthetic data set and on images of handwritten digits, with comparison to classical kernel-PCA and iterative kernel-PCA.
Principal component analysis (PCA) has been widely applied in process monitoring and modeling. The time-varying property of industrial processes requires the adaptive ability of the PCA. This paper introduces a novel ...
详细信息
Principal component analysis (PCA) has been widely applied in process monitoring and modeling. The time-varying property of industrial processes requires the adaptive ability of the PCA. This paper introduces a novel PCA algorithm, named on-line PCA (OLPCA). It updates the PCA model according to the process status. The approximate linear dependence (ALD) condition is used to check each new sample. A recursive algorithm is proposed to reconstruct the PCA model with selected samples. Three types of experiments, a synthetic data, a benchmark problem, and a ball mill load experimental data, are used to illustrate our modeling method. The results show that the proposed OLPCA is computationally faster, and the modeling accuracy is higher than conventional moving window PCA (MWPCA) and recursive PCA (RPCA) for time-varying process modeling. (c) 2011 Elsevier By. All rights reserved.
A novel fiber-optic curvature gage, which can measure curvature directly, has been developed in recent years. In order to measure the bending and torsional deformation of space curve shape, an array of looped fiber-op...
详细信息
A novel fiber-optic curvature gage, which can measure curvature directly, has been developed in recent years. In order to measure the bending and torsional deformation of space curve shape, an array of looped fiber-optic curvature gages are arranged on two symmetrical surfaces of a flexible layer to form a gage layer system. A calibration method of the gage layer system is proposed. Based on the bending curvature and twist values of space curve structure provided by gage layer system, a moving coordinate system is established by curve tangent and curvature vectors through a differential geometry method. The osculating plane is determined by twist angle in the moving coordinate system. The calculation of curve bending and analysis of the moving coordinate system transformation can be carried out in osculating plane. Then, the space curve is divided into many easily analyzed plane curves. recursive algorithm is used to obtain the position information of space curve points and the space curve fitting can be realized. The correlative formulas are deduced and the algorithm is validated by a simulation example. (C) 2011 Elsevier Ltd. All rights reserved.
This paper focuses on the study of dynamic modeling of nonholonomic wheeled mobile robotic manipulators, which consist of a serial manipulator with elastic joints and an autonomous wheeled mobile platform. To avoid co...
详细信息
This paper focuses on the study of dynamic modeling of nonholonomic wheeled mobile robotic manipulators, which consist of a serial manipulator with elastic joints and an autonomous wheeled mobile platform. To avoid computing the Lagrange multipliers associated with the nonholonomic constraints, the approach of Gibbs-Appell (G-A) formulation in recursive form is adopted. For modeling the system completely and precisely, dynamic interactions between the manipulator and the mobile platform, as well as both nonholonomic constraints associated with the no-slipping and the no-skidding conditions, are included. Based on developed formulation, an algorithm is proposed that recursively and systematically derives the equation of motion. In this algorithm, in order to improve the computational complexity, all mathematical operations are done by only 3 x 3 and 3 x 1 matrices. Also, all dynamic expressions of a link are expressed in the same link local coordinate system. Finally, two computational simulations for mobile manipulators with rigid and elastic joints are presented to indicate the capability of this algorithm in generating the equation of motion of mobile robotic manipulators with high degree of freedom. (C) 2012 Sharif University of Technology. Production and hosting by Elsevier B.V. All rights reserved.
A new approach in the design of digital algorithms for simultaneous local system magnitude and frequency estimation of a signal with time-varying frequency is presented. The algorithm is derived using the maximum like...
详细信息
A new approach in the design of digital algorithms for simultaneous local system magnitude and frequency estimation of a signal with time-varying frequency is presented. The algorithm is derived using the maximum likelihood method. The pure sinusoidal voltage model was assumed. The investigation has been simplified because the total similarity to the state of the problem of de offset and frequency estimation has been noticed. Finite impulse response (FIR) digital filters are used to minimize the noise effect and to eliminate the presence of harmonic effects. The algorithm showed a very high level of robustness, as well as high measurement accuracy over a wide range of frequency changes. The algorithm convergence provided fast response and adaptability. This technique provides accurate estimates in about 25 ms and requires modest computations. The theoretical bases of the technique are described. To demonstrate the performance of the developed algorithm, computer-simulated data records are processed. The proposed algorithm has been tested in a laboratory to establish its feasibility in a real-time environment.
To reduce the computational complexity of matrix inversion, which is the majority of processing in many practical applications, two numerically efficient recursive algorithms (called algorithms I and II, respectively...
详细信息
To reduce the computational complexity of matrix inversion, which is the majority of processing in many practical applications, two numerically efficient recursive algorithms (called algorithms I and II, respectively) are presented. algorithm I is used to calculate the inverse of such a matrix, whose leading principal minors are all nonzero. algorithm II, whereby, the inverse of an arbitrary nonsingular matrix can be evaluated is derived via improving the algorithm I. The implementation, for algorithm II or I, involves matrix-vector multiplications and vector outer products. These operations are computationally fast and highly parallelizable. MATLAB simulations show that both recursive algorithms are valid.
This article presents a recursive heuristic algorithm to generate cutting patterns for the rectangular guillotine strip packing problem in which a set of rectangular items must be cut from the strip such that the cons...
详细信息
This article presents a recursive heuristic algorithm to generate cutting patterns for the rectangular guillotine strip packing problem in which a set of rectangular items must be cut from the strip such that the consumed strip length is minimized. The strip is placed with its length along the horizontal direction, and is divided into several segments with vertical cuts. The length of a segment is determined by the item placed at the bottom. Orthogonal cuts divide the segments into blocks and finished items. For the current block considered, the algorithm selects an item, puts it at the bottom-left corner of the block, and divides the unoccupied region into two smaller blocks with an orthogonal cut. Rotation of the items by 90 is allowed. Both lower and upper bounds are used to prune unpromising branches. The computational results indicate that the algorithm performs better than several recently published algorithms.
To generalize the concept of Pade approximation for functions to more than one variable, several definitions have been introduced. We distinguish two types of definitions, the homogeneous multivariate Pade approximati...
详细信息
To generalize the concept of Pade approximation for functions to more than one variable, several definitions have been introduced. We distinguish two types of definitions, the homogeneous multivariate Pade approximation and the general multivariate Pade approximation. Both definitions have advantages and disadvantages. In this work we present a new definition, of the multivariate Pade approximation, adapted to one class of functions. This definition is designed to avoid disadvantages of both definitions. The idea is that special cases deserve special treatment, which will enable approximants to show the character of function to approach and thus reduce the error of approximation and the computation cost. The main result obtained as consequence of this definition is some convergence results of multivariate Stieltjes series and a generalization of the Montessus De Ballore theorem for this class of multivariate functions. (c) 2011 IMACS. Published by Elsevier B.V. All rights reserved.
In this paper, a novel spatial-temporal multi-scale method (STMSM) is proposed to solve the problem of detecting multiple moving objects on complex background. Moving objects have multi-scale features both in spatial ...
详细信息
ISBN:
(纸本)9784990644109;9781467322164
In this paper, a novel spatial-temporal multi-scale method (STMSM) is proposed to solve the problem of detecting multiple moving objects on complex background. Moving objects have multi-scale features both in spatial and temporal domain. The motion salience sub-spaces determine the moving features including position, size and trajectory of each moving object, then the problem of detecting moving objects can be transformed into searching optimal sub-spaces with different scales. This paper proposes a recursive algorithm for estimating motion salience in 3D space and an optimal determinant criterion. These can detect multiple objects at different spatial-temporal scales and extract their features on complex background. The experimental results show this method is effective in detecting multiple moving objects.
暂无评论