The action of the constraint forces over the systems component masses is defined by the

constraint matrix W [member of] [[reals].sup.nxm] ([W.sup.T] = J, the Jacobian) which may be obtained by assembling the constraint vectors w.

in which C is the

constraint matrix and F is the corresponding response constraint vector.

Specifically, we use Q to denote

constraint matrix, where Q(i, j) = 1 if edge ([v.sub.i], [v.sub.j]) [member of] [E.sub.ML], Q(i, j) = -1 if edge ([v.sub.i], [v.sub.j]) [member of] [E.sub.CL], otherwise.

The shape of the household

constraint matrix is as follows:

The Lagrangian method for contact modeling, where nonpenetration condition is strictly and exactly satisfied and the contact force is represented by

constraint matrix and Lagrange multipliers, has also attracted attentions from a lot of researchers [10-13].

Based on Chinese word segmentation based syntax and semantics of the

constraint matrix Chinese word segmentation algorithm and design and a segmentation system.

The graph coloring spectrum allocation model can be described by channel availability matrix, channel reward matrix, interference

constraint matrix, and conflict free channel assignment matrix [30].

Therefore the spectrum allocation model of cognitive wireless network can be expressed in the following matrices: leisure spectrum matrix L (Leisure), benefit matrix B (Benefit),

constraint matrix C (Constraint), and allocation matrix A (Allocation).

C and f are respectively the

constraint matrix and the response vector, which specify the known constraints and the required responses that must be satisfied by the solution.

The weights of an LCMP beamformer are chosen to minimize the output power of the beamformer which subjects to a set of m linear constraints of the form [C.sup.H]w = f, where C is the N x m

constraint matrix, and f is the m x 1 vector of constraint values.

The first four columns of Table 1 present the problem code, the number of rows (constraints), the number of columns (decision variables) and the best known cost value for each instance (IP optimal), and the density (percentage of ones in the

constraint matrix) respectively.