The Discrete Fractional Fourier Transform is a useful tool for multicomponent chirp parameter estimation, however much of the current work ignores the presense of noise. In recent work, a projection-subspace approach to DFrFTbased multicomponent chirp parameter estimation was proposed, to exploit the robustness of subspace decomposition methods. This paper refines the prior projection-subspace ...

Since the seminal paper of Kötter and Kschischang [20] there is a still growing interest in subspace codes, which are sets of subspaces of the Fq-vector space F n q . If all subspaces, which play the role of the codewords, have the same dimension, say k, then one speaks of constant dimension codes. The most commonly used distance measures for subspace codes, motivated by an information-theoreti...

New formulas for the asymptotic variance of the parameter estimates in subspace identi)cation, show that the accuracy of the parameter estimates depends on certain indices of ‘near collinearity’ of the state and future input subspaces of the system to be identi)ed. This complements the numerical conditioning analysis of subspace methods presented in the companion paper (On the ill-conditioning ...

Krylov subspace spectral methods have been shown to be high-order accurate in time and more stable than explicit time-stepping methods, but also more difficult to implement efficiently. This paper describes how these methods can be fashioned into practical solvers by exploiting the simple structure of differential operators Numerical results concerning accuracy and efficiency are presented for ...

The matrix Sylvester equation for congruence, or T-Sylvester equation, has recently attracted considerable attention as a consequence of its close relation to palindromic eigenvalue problems. The theory concerning T-Sylvester equations is rather well understood and there are stable and efficient numerical algorithms which solve these equations for smallto medium-sized matrices. However, develop...

In this paper we analyze the convergence of some commonly used Krylov subspace methods for computing the action of matrix Mittag-Leffler functions. As it is well known, such functions find application in the solution of fractional differential equations. We illustrate the theoretical results by some numerical experiments.

There are many examples where non-orthogonality of a basis for Krylov subspace methods arises naturally. These methods usually require less storage or computational effort per iteration than methods using an orthonormal basis (optimal methods), but the convergence may be delayed. Truncated Krylov subspace methods and other examples of non-optimal methods have been shown to converge in many situ...

A signal eigenvalue sensitivity analysis for subspace-based methods that exploit the shift-invariance property present in the signal subspace is considered. It is proved that signal eigenvalues are rather insensitive to small perturbations in the data provided the dimension of the problem is large enough and the eigenvalues themselves are not extremely close to each other. In addition, bounds o...

Representing images with layers has many important applications, such as video compression, motion analysis, and 3D scene analysis. This paper presents a robust subspace approach to reliably extracting layers from images by taking advantages of the fact that homographies induced by planar patches in the scene form a low dimensional linear subspace. Such subspace provides not only a feature spac...

There has been a great effort to transfer linear discriminant techniques that operate on vector data to high-order data, generally referred to as Multilinear Discriminant Analysis (MDA) techniques. Many existing works focus on maximizing the inter-class variances to intra-class variances defined on tensor data representations. However, there has not been any attempt to employ class-specific dis...