The design of an optimum front-end module for an automatic speech recognition system is still a great effort of many research teams all over the world. Prepared paper wants to contribute partly to these discussions. It is especially aimed at feature decorrelation techniques based on Maximum Linear Likelihood Transform (MLLT) applied at a different level of matrix clustering. Also the comparison...

The noise robustness of an adaptive decorrelation ltering (ADF)-based co-channel speech separation system is addressed. While ADF algorithm has been shown as an effective method in speech-alone scenarios, its performance deteriorates in the presence of background noise. In this work, it is shown that the performance of the ADF-based system deteriorates when the speech-to-noise ratio (SNR) worse...

In this paper, we propose a novel blind-source separation method to extract fetal ECG from a single-channel signal measured on the abdomen of the mother. The signal is a mixture of the fetal ECG, the maternal ECG and noise. The key idea is to project the signal into higher dimensions, and then use an assumption of statistical independence between the components to separate them from the mixture...

PURPOSE Deconvolution based on truncated singular value decomposition (SVD deconvolution) is a promising method for measuring cerebral blood flow (CBF) with dynamic susceptibility contrast-enhanced magnetic resonance imaging (DSC-MRI), but it has proved extremely sensitive to tracer delay. The purpose of this study was to investigate the effect of regional tracer delay on CBF determined by SVD ...

˗Image de-noising is an important challenging issue in image pre-processing. Two popular methods to the problem are partial differential equation (PDE) based nonlinear diffusion method and singular value decomposition (SVD) method. Various image de-noising algorithms based on these two methods have been independently developed. This paper proposes an approach for image de-noising by performing ...

= ' blind sequence detection (BSD) aigorithm based on the innovations approach is proposed and its performance in a Rayleigh fading environment is evaluated. A cornparison between the innovations and Tong's Singular Value Decomposition (SVD) [25] based blind sequence detection algorithm is also presented. Further insight is gained on how blind sequence detectors behave by examining several para...

In this paper a parallel implementation of the SVD{updating algorithm using approximate rotations is presented. In its original form the SVD{updating algorithm had numerical problems if no reorthogonalization steps were applied. Representing the orthogonal matrix V (right singular vectors) using its parameterization in terms of the rotation angles of n(n?1)=2 plane rotations these reorthogonali...

For one isolated wireless link we take a unified look at simple beamforming (BF) as contrasted with MIMO to see how both emerge and under which conditions advantage goes to one or the other. Communication is from a high base array to a user in clutter. The channel propagation model is derived from fundamentals. The base knows the power angular spectrum, but not the channel instantiation. Eigens...

The text retrieval method using latent semantic indexing (LSI) technique with truncated singular value decomposition (SVD) has been intensively studied in recent years. The SVD reduces the noise contained in the original representation of the term–document matrix and improves the information retrieval accuracy. Recent studies indicate that SVD is mostly useful for small homogeneous data collect...

The text retrieval method using Latent Semantic Indexing (LSI) technique with truncated Singular Value Decomposition (SVD) has been intensively studied in recent years. The SVD reduces the noise contained in the original representation of the term-document matrix and improves the information retrieval accuracy. Recent studies indicate that SVD is mostly useful for small homogeneous data collect...