We consider the problem of weak signal detection in strong disturbance with a subspace structure. Unlike conventional subspace detection techniques relying on the availability of a large amount of training data, we consider a knowledge-aided (KA) subspace detection approach for training limited scenarios by incorporating partial prior knowledge of the subspace. A unique feature of the proposed ...

A QR based technique is presented for estimating the approximate numerical rank and corresponding signal subspace of a matrix together with the subspace projection of the least squares weights. Theoretical difficulties associated with conventional QR factorisation are overcome by applying the technique of RowZeroing QR to the covariance matrix. Thresholding is simplified compared with the use o...

The spatio-temporal-prediction (STP) method for multichannel speech enhancement has recently been proposed. This approach makes it theoretically possible to attenuate the residual noise without distorting speech. In addition, the STP method depends only on the second-order statistics and can be implemented using a simple linear filtering framework. Unfortunately, some numerical problems can ari...

The convergence properties of a recently developed recursive subspace identification algorithm are investigated in this paper. The algorithm operates on the basis of an extended instrumental variable (EIV) version of the propagator method for signal subspace estimation. It is proved that, under weak conditions on the input signal and the identified system, the considered MOESP class of recursiv...

The convergence properties of recently developed recursive subspace identification methods are investigated in this paper. The algorithms operate on the basis of instrumental variable (IV) versions of the propagator method for signal subspace estimation. It is proved that, under suitable conditions on the input signal and the system, the considered recursive subspace identification algorithms c...

In this paper the signal subspace approach for nonpara-metric speech enhancement is considered. Several algorithms have been proposed in the litterature but only partly analyzed. Here, the diierent algorithms are compared , and the emphasis is put onto the limiting factors and practical behavior of the estimators. Experimental results show that the signal subspace approach may lead to a signiic...

Singularity of a robot manipulator is one of the obstacles that influences its capabilities. This paper discusses constrained and allowable rotational motion resulting from lost translational freedom when the robot is singular. A convenient method and simple and clear expression to determine the allowable rotational axes and the subspace that they form, under Jacobian singularity, is analyzed a...

We discuss the DPASTd algorithm for signal subspace tracking. Our analysis shows that, under a sufficient condition on the step size, the DPASTd algorithm is locally stable even though delayed updating is applied. A pipelined realization of the algorithm and the corresponding systolic architecture are also proposed and a method for reciprocal computation is discussed. We also present simulation...

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...

Subspace methods are essential to high-resolution environment sensing in the emerging unmanned systems, if further combined with millimeter-wave (mm-Wave) massive multi-input multi-output (MIMO) technique. The estimation of signal/noise subspace, as one critical step, is yet computationally complex and presents a particular challenge when developing low-complexity automotive radars. In this wor...