We consider the problem of determining the order of a parametric model from a noisy signal based on the geometry of the space. More specifically, we do this using the nontrivial angles between the candidate signal subspace model and the noise subspace. The proposed principle is closely related to the subspace orthogonality property known from the MUSIC algorithm, and we study its properties and...

We present in this paper a novel subspace approach for single channel speech enhancement and speech recognition in highly noisy environments. Our algorithm is based on principal component analysis and the optimal subspace selection is provided by a minimum description length criterion. This choice overcomes the limitations encountered with other selection criteria, like the overestimation of th...

System identiication of linear dynamical systems using so-called subspace methods consists of two main steps. First, a signal subspace estimate is found. This usually corresponds to estimating the range space of the extended observability matrix. Then the system parameters are estimated from the subspace estimate. The main result of this note is explicit excitation conditions on the input signa...

We introduce a novel adaptive digital beamforming algorithm for application in cellular CDMA communications systems. A Noniterative Rank-one Signal Subspace eigenstruc-ture Update (NR1SSU) algorithm enables low-complexity re-cursive processing of beamforming weights. A PN chip-level IS-95 CDMA reference model 3] has been used to test the beamforming algorithm via simulation. Our results show th...

In this paper, estimation and tracking of the propagation delays, also known as code acquisition and tracking, in an asynchronous DS-CDMA system are considered. Of special interest is the performance in a near-far environment and the proposed estimator is shown to be near-far resistant. The suggested technique is subspace based and relies on recursively tracking the signal subspace, followed by...

This paper proposes a subspace decomposition method based on an over-complete dictionary in sparse representation, called “sparse signal subspace decomposition” (or 3SD) method. This method makes use of a novel criterion based on the occurrence frequency of atoms of the dictionary over the data set. This criterion, well adapted to subspace decomposition over a dependent basis set, adequately re...

For pathological voices, hoarseness is mainly due to jitter and air flow turbulence in the vocal tract. In this paper, speech denoising is performed in time-domain, by means of a fast and reliable subspace approach. A low-order singular value decomposition allows separating the signal and the noise subspace of an appropriate data matrix, obtained from short data frames. The filtered signal is r...

In this paper, we propose a distributed signal subspace interference alignment algorithm for single beam K − user ( 3 K ≥ ) MIMO interference channel based on sum rate maximization and game theory. A framework of game theory is provided to study relationship between interference signal subspace and altruistic-egoistic bayesian game cost function. We demonstrate that the asymptotic interference ...