In Bio-medical engineering, Electrocardiograph (ECG) has a key importance to diagnose the heart diseases. While acquiring the ECG signal, an Electroencephalography (EEG) interferes the desired ECG signal, due to which the true information can not be retrieved. In this paper, the modified Iterative Version of Adaptive kalman and Recursive Least Square (RLS) Adaptive Filtering algorithms are used...

An adaptive transversal equalizer based on the least-mean-square (LMS) algorithm, operating in an environment with a temporally correlated interference, can exhibit better steady-state mean-square-error (MSE) performance than the corresponding Wiener filter. This phenomenon is a result of the nonlinear nature of the LMS algorithm and is obscured by traditional analysis approaches that utilize t...

We address the problem of estimating time-varying fading channels in filter bank multicarrier (FBMC/OQAM) wireless systems based on pilot symbols. The standard solution to this problem is the least square (LS) estimator or the minimum mean square error (MMSE) estimator with possible adaptive implementation using recursive least square (RLS) algorithm or least mean square (LMS) algorithm. Howeve...

In this paper, we exploit the non-linear relation between a speech source and its associated lip video as a source of extra information to propose an improved audio-visual speech source separation (AVSS) algorithm. The audio-visual association is modeled using a neural associator which estimates the visual lip parameters from a temporal context of acoustic observation frames. We define an objec...

This paper deals with the problem of speech enhancement when a corrupted speech signal with an additive colored noise is the only information available for processing. Kalman filtering is known as an effective speech enhancement technique, in which speech signal is usually modeled as autoregressive (AR) process and represented in the state-space domain. In the above context, all the Kalman filt...

If we try to estimate the parameters of the AR process {Xn} using the observed process {Xn+Zn} then these estimates will be badly biased and not consistent but we can minimize the damage using a robust estimation procedure such as GM-estimation. The question is does additive contamination affect estimates of “core” parameters in the infinite variance case to the same extent that it does in the ...

This paper provides two approaches for design of Generalized Predictive Control (GPC) algorithm for a non-linear dynamic system. In the classical approach of the GPC strategy the recursive method of least square is considered for calculating of the linearized model parameters from the known analytic description of a particular non-linear system. The other purpose of this paper is to show an int...

We present error estimates for the regularized least square algorithm in learning theory in RKHS, using the concept of effective dimensionality.