568 research outputs found
A Semismooth Newton Method for Tensor Eigenvalue Complementarity Problem
In this paper, we consider the tensor eigenvalue complementarity problem
which is closely related to the optimality conditions for polynomial
optimization, as well as a class of differential inclusions with nonconvex
processes. By introducing an NCP-function, we reformulate the tensor eigenvalue
complementarity problem as a system of nonlinear equations. We show that this
function is strongly semismooth but not differentiable, in which case the
classical smoothing methods cannot apply. Furthermore, we propose a damped
semismooth Newton method for tensor eigenvalue complementarity problem. A new
procedure to evaluate an element of the generalized Jocobian is given, which
turns out to be an element of the B-subdifferential under mild assumptions. As
a result, the convergence of the damped semismooth Newton method is guaranteed
by existing results. The numerical experiments also show that our method is
efficient and promising
Tensor Network alternating linear scheme for MIMO Volterra system identification
This article introduces two Tensor Network-based iterative algorithms for the
identification of high-order discrete-time nonlinear multiple-input
multiple-output (MIMO) Volterra systems. The system identification problem is
rewritten in terms of a Volterra tensor, which is never explicitly constructed,
thus avoiding the curse of dimensionality. It is shown how each iteration of
the two identification algorithms involves solving a linear system of low
computational complexity. The proposed algorithms are guaranteed to
monotonically converge and numerical stability is ensured through the use of
orthogonal matrix factorizations. The performance and accuracy of the two
identification algorithms are illustrated by numerical experiments, where
accurate degree-10 MIMO Volterra models are identified in about 1 second in
Matlab on a standard desktop pc
A regularization-patching dual quaternion optimization method for solving the hand-eye calibration problem
The hand-eye calibration problem is an important application problem in robot
research. Based on the 2-norm of dual quaternion vectors, we propose a new dual
quaternion optimization method for the hand-eye calibration problem. The dual
quaternion optimization problem is decomposed to two quaternion optimization
subproblems. The first quaternion optimization subproblem governs the rotation
of the robot hand. It can be solved efficiently by the eigenvalue decomposition
or singular value decomposition. If the optimal value of the first quaternion
optimization subproblem is zero, then the system is rotationwise noiseless,
i.e., there exists a ``perfect'' robot hand motion which meets all the testing
poses rotationwise exactly. In this case, we apply the regularization technique
for solving the second subproblem to minimize the distance of the translation.
Otherwise we apply the patching technique to solve the second quaternion
optimization subproblem. Then solving the second quaternion optimization
subproblem turns out to be solving a quadratically constrained quadratic
program. In this way, we give a complete description for the solution set of
hand-eye calibration problems. This is new in the hand-eye calibration
literature. The numerical results are also presented to show the efficiency of
the proposed method
Identification of Genes and Pathways Involved in Alveolar Epithelial Cell Differentiation Using Dna Microarray
In this project, genes and pathways involved in lung alveolar epithelial cell (AEC) differentiation were identified. In-house printed DNA microarray, data analysis software (RealSpot) and multiple sample hybridization system were developed. These tools were tested at organ and cell level with biological samples from rats. Differentially expressed genes during AEC differentiation were identified using the tested tools and a rat model of hyperoxia exposure and recovery. Data from DNA microarray were verified at mRNA level with real-time PCR, at protein level with Western blot, and at cell level with in vitro/ AEC culture. Pathways based on the verified genes were proposed to elucidate the mechanisms of AEC differentiation. (1)At organ level, 147 genes are expressed predominantly in lung by directly comparing transcriptomes of lung, heart, kidney, liver, spleen and brain. (2)At cell level, P2X7 and GABRP are potential type I AEC (AEC I) and type II AEC (AEC II) markers. Among the 1080 AEC I- and 1142 II-Veterinary Pathobiolog
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