There are various image filtering approaches in computer vision and image processing that are effective for some types of noise, but they invariably make certain assumptions about the properties of the signal and/or noise which lack the generality for diverse image noise reduction. This study describes a novel generalised guided image filtering method with the reference image generated by signa...

A blind deconvolution algorithm is introduced. The channel parameters are identi ed based on Maximum Likelihood (ML) criterion and the desired input is estimated using minimum variance estimation. Simulation results show the e cacy of our method. Its estimation error is usually less than other algorithms. Its rate of convergence is su ciently high and compete the others. Although, the algorithm...

Semiparametric estimation of the signal subspace∗ Denis Belomestny, Vladimir Panov, Vladimir Spokoiny 1 — Laboratory for Structural Methods of Data Analysis in Predictive Modeling (MIPT) and University Duisburg-Essen, [email protected] 2 — Laboratory for Structural Methods of Data Analysis in Predictive Modeling (MIPT) and University Duisburg-Essen, [email protected] 3 — Labor...

a r t i c l e i n f o a b s t r a c t This paper presents a new time domain noise reduction approach based on Singular Value Decomposition (SVD) technique. In the proposed approach, the noisy signal is initially represented in a Hankel Matrix. Then SVD is applied on the Hankel Matrix to divide the data into signal subspace and noise subspace. Since singular vectors are the span bases of the mat...

This paper deals with the decoupling problems of unknown, measurable, and previewed signals. First, well-known solutions of unknown and measurable disturbance decoupling problems are recalled. Then, new necessary and sufficient constructive conditions for the previewed signal decoupling problem are proposed. The discrete-time case is considered. In this domain, previewing a signal by p steps me...

This paper deals with the performance of blind multiuser detectors for CDMA is analyzed. The blind multiuser detectors are Direct Matrix Inversion (DMI) blind detector and subspace blind detector. The performance analysis is performed by means of the Signal to Interference Noise Ration (SINR) and Bit Error Rate (BER). The numerical results are plotted as variation of SINR Vs SNR and ρ , SINR wi...

A novel approach is proposed in order to reduce the number of sweeps (trials) required for the efficient extraction of the brain evoked potentials (EPs). This approach is developed by combining both the Wiener filtering and the subspace methods. First, the signal subspace is estimated by applying the singularvalue decomposition (SVD) to an enhanced version of the raw data obtained by Wiener fil...

In this study, the Direction Of Departure (DOD) and Arrival (DOA) of signals detection for Multi-Input Multi-Output (MIMO) radar is discussed. A novel signal subspace reconstruction model to match obtained based on covariance matrix array output developed enhance performance DOD DOA detection. scheme, technology beamforming first introduced define an objective space in mathematics targets be de...

In this paper we utilize the gamma neural model to improve the signal to noise ratio (SNR) of broadband signals corrupted by white noise. The projection of a noisy signal onto the signal subspace can not remove the noise in the subspace. A focus gamma network, when trained as a nonlinear predictor of the projected trajectory, reduces this noise further. The property of adaptive memory depth of ...