A novel subspace approach for speech enhancement using a subband whitening filter is proposed. Previous subspace approaches for enhancement either assumed white noise or used a fullband pre-whitening filter before enhancement for colored noise. The previous approaches were successful only in reducing the upper bound of the signal distortion while reducing noise. However, the proposed method min...

In this paper, we introduce subspace-frequently hypercyclic operators. We show that these operators are subspace-hypercyclic and there are subspace-hypercyclic  operators that are not subspace-frequently hypercyclic. There is a criterion like to subspace-hypercyclicity criterion that implies subspace-frequent hypercyclicity and if an operator $T$ satisfies this criterion, then $Toplus T$ is sub...

In this paper, we study two types of the reducing subspaces for the weighted composition operator $W: frightarrow ucdot fcirc varphi$ on $L^2(Sigma)$. A necessary and sufficient condition is given for $W$ to possess the reducing subspaces of the form $L^2(Sigma_B)$ where $Bin Sigma_{sigma(u)}$. Moreover, we pose some necessary and some sufficient conditions under which the subspaces of the form...

A novel technique is presented to design the signal subspace speech enhancement based on perceptual post filtering. Firstly, by subspace filter the noisy speech is enhanced. The underlying principle is to decompose the vector space of the noisy signal into a signal plus noise subspace and a noise subspace. The decomposition can theoretically be performed by applying the Karhunen-Loeve transform...

A sequence ${T_n}_{n=1}^{infty}$ of bounded linear  operators on a separable infinite dimensional Hilbert space $mathcal{H}$ is called subspace-diskcyclic with respect to the closed subspace $Msubseteq mathcal{H},$ if there exists a vector $xin mathcal{H}$ such that the disk-scaled orbit ${alpha T_n x: nin mathbb{N}, alpha inmathbb{C}, | alpha | leq 1}cap M$ is dense in $M$. The goal of t...

In this paper, a speech classifier inspired by the signal subspace approach is developed. A novel signal subspace speech model is initially obtained via a rank reducing subspace decomposition algorithm that is based on the SVD. Motivated by the assumption that the speech signal comprises of short term dynamics that are slowly changing, it follows that the signal subspace of the speech signal is...

In this paper, we represent an inexact inverse subspace iteration method for computing a few eigenpairs of the generalized eigenvalue problem Ax = Bx [Q. Ye and P. Zhang, Inexact inverse subspace iteration for generalized eigenvalue problems, Linear Algebra and its Application, 434 (2011) 1697-1715 ]. In particular, the linear convergence property of the inverse subspace iteration is preserved.