MULTI-LAYER TRACK FUSION ALGORITHM BASED ON SUPPORTING DEGREE MATRIX

The random noises of multi-sensor and the environment make observations uncertain and correlative, so the performance of fusion algorithms is reduced by using observations directly. To solve this problem, a multi-layer track fusion algorithm based on supporting degree matrix is proposed. Combined with the track fusion algorithm based on filtering step by step, it uses multi-sensor observations to establish supporting degree matrix and realize multi-layer fusion. Simulation results show its estimation precision is higher than the original algorithm and is increased by 20% around. Therefore, it solves the problem of target tracking further in the distributed track fusion system.

Transmission Index Research of Parallel Manipulators Based on Matrix Orthogonal Degree

Performance index mance evaluation, and is the is the standard of perfor- foundation of both perfor- mance analysis and optimal design for the parallel manipulator. Seeking the suitable kinematic indices is always an important and challenging issue for the parallel manipulator. So far, there are extensive studies in this field, but few existing indices can meet all the requirements, such as simple, intuitive, and universal. To solve this problem, the matrix orthogonal degree is adopted, and generalized transmission indices that can evaluate motion/force trans- missibility of fully parallel manipulators are proposed. Transmission performance analysis of typical branches, end effectors, and parallel manipulators is given to illus- trate proposed indices and analysis methodology. Simula- tion and analysis results reveal that proposed transmission indices possess significant advantages, such as normalized finite （ranging from 0 to l）, dimensionally homogeneous, frame-free, intuitive and easy to calculate. Besides, pro- posed indices well indicate the good transmission region and relativity to the singularity with better resolution than the traditional local conditioning index, and provide a novel tool for kinematic analysis and optimal design of fully parallel manipulators.

Applying Possibility Degree Method for Ranking Interval Numbers to Partnership Selection

A new interval number ranking approach is applied for assessment of priorities of the alternative partners, where the attribute values are given out as interval numbers while the weight of each criterion is still exact numerical value pattern. After aggregating with the weighted arithmetic averaging operator, the result is still in the form of interval number. To achieve the priorities of alternative partners we take the possibility method for ranking interval numbers into account which could derive priorities from inconsistent attribute values, thus eliminating the adjustment to the inconsistent attribute values. Moreover, this method is very simple and needs less calculation. An illustrative example is given out to demonstrate this smart method.

Fuzzy Optimum Model of Semi-Structural Decision for Lectotype Optimization of Offshore Platforms

In the process of concept design of offshore platforms, it is necessary to select the best from feasible alternatives through comparison and filter. The criterion set, used to evaluate and select the satisfying alternative, consists of many qualitative and quantitative factors. Therefore, the selection is a problem of multicriteria and semi-structural decision-making. Different from traditional methods in semi-structural decision-making, a new framework and methodology is presented in this paper for evaluation of offshore platform alternatives, First, the criterion set is established for the evaluation of alternatives. Next, the approach is studied to construct the relative membership degree matrix, in which both qualitative and quantitative factors are consistent with the uniform calculating standard. And then a new weight-assessing method is developed for calculation of the weights based on the relative membership degree matrix. Finally, a multi-hierarchy fuzzy optimum model is adopted to select the satisfying offshore platform alternative. A case study shows that the new framework and methodology are scientific, reasonable and easy to use in practice.

Degrees of freedom in low rank matrix estimation

The objective of this paper is to quantify the complexity of rank and nuclear norm constrained methods for low rank matrix estimation problems. Specifically, we derive analytic forms of the degrees of freedom for these types of estimators in several common settings. These results provide efficient ways of comparing different estimators and eliciting tuning parameters. Moreover, our analyses reveal new insights on the behavior of these low rank matrix estimators. These observations are of great theoretical and practical importance. In particular, they suggest that, contrary to conventional wisdom, for rank constrained estimators the total number of free parameters underestimates the degrees of freedom, whereas for nuclear norm penalization, it overestimates the degrees of freedom. In addition, when using most model selection criteria to choose the tuning parameter for nuclear norm penalization, it oftentimes suffices to entertain a finite number of candidates as opposed to a continuum of choices. Numerical examples are also presented to illustrate the practical implications of our results.

Degree dependence entropy descriptor for complex networks

In order to supply better accordance for mod eling and simulation of complex networks, a new degree dependence entropy （DDE） descriptor is proposed to describe the degree dependence relationship and corre sponding characteristic in this paper. First of all, degrees of vertices and the shortest path lengths between all pairs of ,ertices are computed. Then the degree dependence matrices under different shortest path lengths are con structed. At last the DDEs are extracted from the degree dependence matrices. Simulation results show that the DDE descriptor can reflect the complexity of degree dependence relationship in complex networks; high DDE indicates complex degree dependence relationship; low DDE indicates the opposite one. The DDE can be seen as a quantitative statistical characteristic, which is meaningful for networked modeling and simulation.

Remarks on the Number of Rational Points on a Class of Hypersurfaces over Finite Fields

Let Fq be the finite field of q elements and f be a nonzero polynomial over Fq. For each b ∈ Fq, let Nq（f = b） denote the number of Fq-rational points on the affine hypersurface f = b. We obtain the formula of Nq（f= b） for a class of hypersurfaces over Fq by using the greatest invariant factors of degree matrices under certain cases, which generalizes the previously known results. We also give another simple direct proof to the known results.

Research on a Class of Equations overFinite Fields

Let Fq stand for the finite field of odd characteristic p with q elements（q=pn,n∈N）and Fq＊ denote the set of all the nonzero elements of Fq.In this paper,by using the augmented degree matrix and the result given by Cao,we obtain a formula for the number of rational points of the following equation over Fq：f（x 1,x 2,...,x n）=（a1 x1 x2d＋a2 x2 x3d...＋a（n-1）x（n-1）xnd＋an xn x1d）λ-bx1（d1）x2d2...xn（dn）,with ai,b∈Fq＊,n≥2,λ〉0 being positive integers,and d,di being nonnegative integers for 1≤i n.This technique can be applied to the polynomials of the form h1λ=h2 with λ being positive integer and h1,h2∈Fq[x 1,x 2,...,x n].It extends the results of the Markoff-Hurwitz-type equations.