ECG signals have been proven a very versatile tool for detection of cardiovascular diseases. But during recording of these signals, the ECG data gets contaminated by various noise signals caused by power line interference, base line wander, electrode movement, muscle movement (EMG) etc. These noise signals are known as artifacts. These artifacts mislead the diagnosis of heart which is not desir...

An improved adaptive equalizer based on the principle of minimum mean square error (MMSE) is proposed. This optimization problem which is shown to be convex, is transformed to second-order cone (SOC) and solved using the interior point method instead of conventional iterative methods such as least mean squares (LMS) or recursive least squares (RLS). To validate its performance a single-carrier ...

In this paper a module consisting of a Fast Least Mean Square (FLMS) filter is modeled and verified to eliminate acoustic echo, which is a problem for hands free communication. However the acoustic echo cancellation (AEC) is modeled using digital signal processing technique especially Simulink Blocksets. The needed algorithm code is generated in Matlab Simulink programming. At the simulation le...

We propose a recursive generalized total least-squares (RGTLS) estimator that is used in parallel with a noise covariance estimator (NCE) to solve the errors-in-variables problem for multi-input-single-output linear systems with unknown noise covariance matrix. Simulation experiments show that the suggested RGTLS with NCE procedure outperforms the common recursive least squares (RLS) and recurs...

In this paper, we exploit the one-to-one correspondences between the recursive least-squares (RLS) and Kalman variables to formulate extended forms of the RLS algorithm. Two particular forms of the extended RLS algorithm are considered: one pertaining to a system identification problem and the other pertaining to the tracking of a chirped sinusoid in additive noise. For both of these applicatio...

We present a methodology for adaptive ltering and system identi cation under the cyclostationary regime. Our technique is based on a deterministic periodic least-squares criterion, and gives rise to adaptive periodic recursive-least-squares (P-RLS) algorithms. Furthermore, we show that every adaptive RLS algorithm has a P-RLS counterpart, which has exactly the same architecture and the same per...

Recently developed recursive least squares schemes, where the square root of both the covariance and the information matrix are stored and updated, are known to be particularly suited for parallel implementation. However, when finite precision arithmetic is used, round-off errors apparently accumulate unboundedly, so that after a number of updates the computed least squares solutions turn out t...

A novel noncoherent receiver for M{ary di erential phase shift{keying (MDPSK) signals transmitted over intersymbol interference (ISI) channels is presented. The noncoherent receiver consists of a linear equalizer and a decision{feedback di erential detector. A signi cant performance gain over a previously proposed noncoherent receiver can be observed. For an in nite number of feedback symbols, ...

In this paper we present conventional and translation-invariant (TI) wavelet-based approaches for single-trial evoked potential estimation based on intracortical recordings. We demonstrate that the wavelet-based approaches outperform several existing methods including the Wiener filter, least mean square (LMS), and recursive least squares (RLS), and that the TI wavelet-based estimates have high...