A strong limit theorem on thissequences is proved on the certain partial set by using the convergence theorem of martingale difference and the property of conditional expectation .

Using the method of closing in on prototype body by partial set of tangent planes the shape reverse seeking based on point cloud of scattered data has been carried out.

On Combinatorial Approximation of Covering 0-1 Integer Programs and Partial Set Cover

Two full sets repeats and one partial set repeat of independent experiments were conducted and all produced similar results.

We continue the investigation of labeled partial (set) 2-structures initiated in [5] and in particular we explore applications to the theory of net-based concurrent systems.

Part I of this paper investigates the basic theory of labeled partial 2-structures and it considers the problem of representing partial 2-structures as partial set 2-structures.

In particular, a subclass of labeled partial 2-structures, the so-called labeled partial set 2-structures corresponds very closely to those graphs that are state spaces of concurrent systems.

The accurate mathematical models for complicated structures are very diffi-cult to construct.The work presented here provides an indentification method for estimating the mass.damping, and stiffness matrices of linear dynamical systems from incomplete experimental data.The mas stiffness.and damping matrices are assumed to be real,symmetric,and posititve definite.The partial set of experimental complex eigenvalues and corresponding eigenvectors are given。In the proposed method the least squares algorithm...

The accurate mathematical models for complicated structures are very diffi-cult to construct.The work presented here provides an indentification method for estimating the mass.damping, and stiffness matrices of linear dynamical systems from incomplete experimental data.The mas stiffness.and damping matrices are assumed to be real,symmetric,and posititve definite.The partial set of experimental complex eigenvalues and corresponding eigenvectors are given。In the proposed method the least squares algorithm is combined with the iteration technique to determine system's indentified matrices and corresponding design parameters.Several illustrative examples,are presented to demonstrate the reli-ability of the proposed method.It is emphasized that the mass,damping and stiffness matrices can be identified simultaneously.

The accurate mathematical models for complicated structures are verydifficult to construct.The work presented here provides an identification method for estimating the mass, damping , and stiffness matrices of linear dynamical systems from incompleteexperimental data. The mass, stiffness, and damping matrices are assumed to be real,symmetric, and positive definite. The partial set of experimental complex eigenvalues and corresponding eigenvectors are given. In the proposed method the least squaresalgorithm...

The accurate mathematical models for complicated structures are verydifficult to construct.The work presented here provides an identification method for estimating the mass, damping , and stiffness matrices of linear dynamical systems from incompleteexperimental data. The mass, stiffness, and damping matrices are assumed to be real,symmetric, and positive definite. The partial set of experimental complex eigenvalues and corresponding eigenvectors are given. In the proposed method the least squaresalgorithm is combined with the iteration technique to determine systems identified matrices and corresponding design parameters. several illustrative examples, are presented to demonstrate the reliability of the proposed method .It is emphasized thatthe mass, damping and stiffness martices can be identified simultaneously.

The accurate mathematical models for complicated structures are very difficult to construct.The work presented here provides an identification method for estimating the mass.damping,and stiffness matrices of linear dynamical systems from incomplete experimental data.The mass,stiffness and damping matrices are assumed to be real,symmetric,and positive definite The partial set of experimental complex eigenvalues and corresponding eigenvectors are given.In the proposed method the least squares algorithm is...

The accurate mathematical models for complicated structures are very difficult to construct.The work presented here provides an identification method for estimating the mass.damping,and stiffness matrices of linear dynamical systems from incomplete experimental data.The mass,stiffness and damping matrices are assumed to be real,symmetric,and positive definite The partial set of experimental complex eigenvalues and corresponding eigenvectors are given.In the proposed method the least squares algorithm is combined with the iteration technique to determine systems identified matrices and corresponding design parameters.Seeveral illustative examples,are presented to demonstrate the reliability of the proposed method .It is emphasized that the mass,damping and stiffness matrices can be identified simultaneously.