Jordan Left Derivations of Generalized Matrix Algebras

In this paper, it is proved that under certain conditions, each Jordan left derivation on a generalized matrix algebra is zero and each generalized Jordan left derivation is a generalized left derivation.

Co-commuting Mappings of Generalized Matrix Algebras

Let G be a generalized matrix algebra over a commutative ring R and Z（G） be the center of G. Suppose that F, T ：G→G are two co-commuting R-linear mappings, i.e., F（x）x = xT（x） for all x ∈ G. In this note, we study the question of when co-commuting mappings on G are proper.

Perfect Matrix Algebras ∑(λ)(Ⅱ)-AK-Property

In this paper, we introduce the concept of AK-property for the perfect ma-trix algebras ∑(λ) and give some characterizations of∑(λ)possessing AK-property.

Local Jordan Derivations and Local Jordan Automorphisms of Upper Triangular Matrix Algebras

Let R be a commutative ring with identity, Tn （R） the R-algebra of all upper triangular n by n matrices over R. In this paper, it is proved that every local Jordan derivation of Tn （R） is an inner derivation and that every local Jordan automorphism of Tn（R） is a Jordan automorphism. As applications, we show that local derivations and local automorphisms of Tn （R） are inner.

Representations of Frobenius-type Triangular Matrix Algebras

The aim of this paper is mainly to build a new representation-theoretic realization of finite root systems through the so-called Frobenius-type triangular matrix algebras by the method of reflection functors over any field. Finally, we give an analog of APR-tilting module for this class of algebras. The major conclusions contains the known results as special cases, e.g., that for path algebras over an algebraically closed field and for path algebras with relations from symmetrizable cartan matrices. Meanwhile, it means the corresponding results for some other important classes of algebras, that is, the path algebras of quivers over Frobenius algebras and the generalized path algebras endowed by Frobenius algebras at vertices.

Piecewise Hereditary Triangular Matrix Algebras

For any positive integer N,we clearly describe all finite-dimensional algebras A such that the upper triangular matrix algebras TN(A)are piecewise hereditary.Consequently,we describe all finite-dimensional algebras A such that their derived categories of N-complexes are triangulated equivalent to derived categories of hereditary abelian categories,and we describe the tensor algebras A⊗K[X]/(X^(N))for which their singularity categories are triangulated orbit categories of the derived categories of hereditary abelian categories.

MATRIX ALGEBRA ALGORITHM OF STRUCTURE RANDOM RESPONSE NUMERICAL CHARACTERISTICS

A new algorithm of structure random response numerical characteristics, namedas matrix algebra algorithm of structure analysis is presented. Using the algorithm, structurerandom response numerical characteristics can easily be got by directly solving linear matrixequations rather than structure motion differential equations. Moreover, in order to solve thecorresponding linear matrix equations, the numerical integration fast algorithm is presented. Thenaccording to the results, dynamic design and life-span estimation can be done. Besides, the newalgorithm can solve non-proportion damp structure response.

On the Solutions of the Matrix Equations in Optimal Stochastic Control

In this paper, the matrix algebraic equations involved in the optimal control problem of time-invariant linear Ito stochastic systems, named Riccati- Ito equations in the paper, are investigated. The necessary and sufficient condition for the existence of positive definite solutions of the Riccati- Ito equations is obtained and an iterative solution to the Riccati- Ito equations is also given in the paper thus a complete solution to the basic problem of optimal control of time-invariant linear Ito stochastic systems is then obtained. An example is given at the end of the paper to illustrate the application of the result of the paper.

DIRECT PERTURBATION METHOD FOR REANALYSIS OF MATRIX SINGULAR VALUE DECOMPOSITION

The perturbational reanalysis technique of matrix singular value decomposition is applicable to many theoretical and practical problems in mathematics, mechanics, control theory, engineering, etc.. An indirect perturbation method has previously been proposed by the author in this journal, and now the direct perturbation method has also been presented in this paper. The second-order perturbation results of non-repeated singular values and the corresponding left and right singular vectors are obtained. The results can meet the general needs of most problems of various practical applications. A numerical example is presented to demonstrate the effectiveness of the direct perturbation method.

MATRIX PERTURBATION METHOD FOR THE VIBRATION PROBLEM OF STRUCTURES WITH INTERVAL PARAMETERS

When the parameters of structures are uncertain, the structural natural frequencies become uncertain. The interval parameters description, i.e. the unknown-but bounded parameters description is one of the methods to study the uncertainty. In this paper, the vibration problem of structure with interval parameters was studied, and the eigenvalue problem of the structures with interval parameters was transferred into two different eigenvalue problems. The perturbation method was applied to the vibration problem of the structures with interval parameters. The numerical results show that the proposed method is sufficiently accurate and needs less computational efforts.

TOPOLOGICAL AND GEOMETRIC PROPERTY OF MATRIX ALGEBRA

Let B（R^n） be the set of all n x n real matrices, Sr the set of all matrices with rank r, 0 ≤ r ≤ n, and Sr^# the number of arcwise connected components of Sr. It is well-known that Sn =GL（R^n） is a Lie group and also a smooth hypersurface in B（R^n） with the dimension n × n.

PERTURBATION METHOD FOR REANALYSIS OF THE MATRIX SINGULAR VALUE DECOMPOSITION

The perturbation method for the reanalysis of the singular value decomposition (SVD) of general real matrices is presented in this paper. This is a simple but efficient reanalysis technique for the SVD, which is of great worth to enhance computational efficiency of the iterative analysis problems that require matrix singular value decomposition repeatedly. The asymptotic estimate formulas for the singular values and the corresponding left and right singular vectors up to second-order perturbation components are derived. At the end of the paper the way to extend the perturbation method to the case of general complex matrices is advanced.

Multiple Regression and Big Data Analysis for Predictive Emission Monitoring Systems

Predictive Emission Monitoring Systems (PEMS) offer a cost-effective and environmentally friendly alternative to Continuous Emission Monitoring Systems (CEMS) for monitoring pollution from industrial sources. Multiple regression is one of the fundamental statistical techniques to describe the relationship between dependent and independent variables. This model can be effectively used to develop a PEMS, to estimate the amount of pollution emitted by industrial sources, where the fuel composition and other process-related parameters are available. It often makes them sufficient to predict the emission discharge with acceptable accuracy. In cases where PEMS are accepted as an alternative method to CEMS, which use gas analyzers, they can provide cost savings and substantial benefits for ongoing system support and maintenance. The described mathematical concept is based on the matrix algebra representation in multiple regression involving multiple precision arithmetic techniques. Challenging numerical examples for statistical big data analysis, are investigated. Numerical examples illustrate computational accuracy and efficiency of statistical analysis due to increasing the precision level. The programming language C++ is used for mathematical model implementation. The data for research and development, including the dependent fuel and independent NOx emissions data, were obtained from CEMS software installed on a petrochemical plant.

Blind recognition of k/n rate convolutional encoders from noisy observation

Blind recognition of convolutional codes is not only essential for cognitive radio, but also for non-cooperative context. This paper is dedicated to the blind identification of rate k/n convolutional encoders in a noisy context based on Walsh-Hadamard transformation and block matrix (WHT-BM). The proposed algorithm constructs a system of noisy linear equations and utilizes all its coefficients to recover parity check matrix. It is able to make use of fault-tolerant feature of WHT, thus providing more accurate results and achieving better error performance in high raw bit error rate (BER) regions. Moreover, it is more computationally efficient with the use of the block matrix (BM) method. ? 2017 Beijing Institute of Aerospace Information.

Application of Petri Net to Fault Diagnosis in Satellite

A prototype of fault diagnosis based on Petri net, which is developed for a satellite tele-control subsystem, is introduced in this paper. Its structure is first given with the emphasis on a Petri net modeling tool which is designed using the object oriented method. The prototype is connected to the database with DAO (Date Access Object) technique, and makes the Petri net's firing mechanism and its analyzing methods to be packed up as DLL (Dynamic Link Library) documents. Compared with the rule-based expert system method, the Petri net-based one can store the knowledge in mathematical matrix and make inference more quickly and effectively.

Direction-of-arrival estimation for uniform circular arrays under small sample size

With a small number of snapshots, performances of uniform circular array (UCA) root-MUSIC based methods for directionof- arrival (DOA) estimation suffer serious degradation, because the beamspace sample covariance matrix (BSCM) severely deviates from the true one. To solve this problem, an iterative technique is proposed. The proposed technique has two key points: transform array data into beamspace data and construct a BSCM; modify the BSCM repeatedly by removing the residual parts. Meanwhile, error and beamspace leakage associated with the BSCM are investigated. The proposed technique can significantly reduce the error and the beamspace leakage which in turn could improve the performance for DOA estimation. Simulation results are given to illustrate the superiority of the proposed technique for uncorrelated and correlated signals. ? 2016 Beijing Institute of Aerospace Information.

Characteristic Polynomial Assignment in 2-D System

The closed loop polynomial assignment problems of 2D systems Roesser model with multiple inputs were studied. The problems were transferred to a rational map and were assigned a sate feedback and output feedback. Sufficient conditions for the system were derived using the algebraic geometric methods.

Fuzzy MCDM Based on Fuzzy Relational Degree Analysis

This paper presents a new fuzzy multiple criteria (both qualitative and quantitative) decision-making (MCDM) method based on fuzzy relational degree analysis. The concepts of fuzzy set theory are used to construct a weighted suitability decision matrix to evaluate the weighted suitability of different alternatives versus various criteria. The positive ideal solution and negative ideal solution are then obtained by using a method of ranking fuzzy numbers, and the fuzzy relational degrees of different alternative versus positive ideal solution and negative ideal solution are calculated by using the proposed arithmetic. Finally, the relative relational degrees of various alternatives versus positive ideal solution are ranked to determine the best alternative. A numerical example is provided to illustrate the proposed method.

Automatic Method for Synchronizing Workpiece Frames in Twin-robot Nondestructive Testing System

The workpiece frames relative to each robot base frame should be known in advance for the proper operation of twin-robot nondestructive testing system. However, when two robots are separated from the workpieces, the twin robots cannot reach the same point to complete the process of workpiece frame positioning. Thus, a new method is proposed to solve the problem of coincidence between workpiece frames. Transformation between two robot base frames is initiated by measuring the coordinate values of three non-collinear calibration points. The relationship between the workpiece frame and that of the slave robot base frame is then determined according to the known transformation of two robot base frames, as well as the relationship between the workpiece frame and that of the master robot base frame. Only one robot is required to actually measure the coordinate values of the calibration points on the workpiece. This requirement is beneficial when one of the robots cannot reach and measure the calibration points. The coordinate values of the calibration points are derived by driving the robot hand to the points and recording the values of top center point（TCP） coordinates. The translation and rotation matrices relate either the two robot base frames or the workpiece and master robot. The coordinated are solved using the measured values of the calibration points according to the Cartesian transformation principle. An optimal method is developed based on exponential mapping of Lie algebra to ensure that the rotation matrix is orthogonal. Experimental results show that this method involves fewer steps, offers significant advantages in terms of operation and time-saving. A method used to synchronize workpiece frames in twin-robot system automatically is presented.

Texture invariant estimation of equivalent number of looks based on log-cumulants in polarimetric radar imagery

A novel estimation of the equivalent number of looks (ENL) is proposed in statistical modeling of multilook polarimetric synthetic aperture radar (PolSAR) images for the product model, which is based on the log-determinant moments (LDM). The LDM estimators discovered by looking at certain log-cumulants of the intensities of different polarization channels and the multilook polarimetric covariance matrix, which can be used for both the Gaussian model and all product models. This estimator has analytic expressions, and uses the full covariance matrix and intensities as input, which makes more statistical information available. Experiments based on simulated data and real data are performed. The comparisons among the widely used methods of equivalent number of looks (ENL) estimation for the product model such as K and G0 distributions show that the performance of the LDM estimator is outstanding. The performance of estimators for the real data of San Francisco and Flevoland is analyzed and the results are according to those of simulated data. Finally, it can be concluded that the LDM estimator is well robust to each product model with low computational complexity and high accuracy. ? 1990-2011 Beijing Institute of Aerospace Information.