efficient mode shape extraction of fluid-structure systems is of particular interest in engineering. an efficient modified version of unsymmetric lanczos method is proposed in this paper. the original unsymmetric lanczos method was applied to general form of unsymmetric matrices, while the proposed method is developed particularly for the fluid-structure matrices. the method provides us with si...

This paper investigates the structure of general affine subspaces of ( )  L . For a d × d expansive matrix A, it shows that every affine subspace can be decomposed as an orthogonal sum of spaces each of which is generated by dilating some shift invariant space in this affine subspace, and every non-zero and non-reducing affine subspace is the orthogonal direct sum of a reducing subspace and a ...

Subspace analysis in computer vision is a generic name to describe a general framework for comparison and classification of subspaces. A typical approach in subspace analysis is the subspace method (SM) that classify an input pattern vector into several classes based on the minimum distance or angle between the input pattern vector and each class subspace, where a class subspace corresponds to ...

The paper presents a model predictive control method for continuous-time systems based on subspace identification. It’s developed by reformulating the continuous-time systems using Laguerre filters to obtain the subspace prediction output. Then, the subspace predictors are derived by QR decomposition from input-output and Laguerre matrices. The subspace predictive controller is designed with th...

The speech enhancement techniques are often employed to improve the quality and intelligibility of the noisy speech signals. This paper discusses a novel technique for speech enhancement which is based on Singular Value Decomposition. This implementation utilizes a Genetic Algorithm based optimization method for reducing the effects of environmental noises from the singular vectors as well as t...

Let Mn(R) and Sn(R) be the spaces of n × n real matrices and real symmetric matrices respectively. We continue to study d(n, n − 2,R): the minimal number such that every -dimensional subspace of Sn(R) contains a nonzero matrix of rank n−2 or less. We show that d(4, 2,R) = 5 and obtain some upper bounds and monotonicity properties of d(n, n − 2,R). We give upper bounds for the dimensions of n − ...

Analysis of high dimensional data is a research area since many years. Analysts can detect similarity of data points within a cluster. Subspace clustering detects useful dimensions in clustering high dimensional dataset. Visualization allows a better insight of subspace clusters. However, displaying such high dimensional database clusters on the 2-dimensional display is a challenging task. We p...

Subspace based estimates, i.e. estimates obtained by exploiting the orthogonality between a sample subspace and a parameter-dependent subspace have proved useful in many applications, including array processing and system identification. The purpose of this contribution is to complement the already available theoretical results generally obtained in specific contexts. We discuss the generalizat...

The robustness of a subspace generalized likelihood ratio test (GLRT) detector to signal mismatch is addressed for data conforming to the generalized multivariate analysis of variance model. This model assumes a deterministic signal of known form in the presence of unknown, colored, Gaussian noise. The subspace GLRT compresses data into a lower-dimensional subspace prior to detection. It is sho...