This paper is focused on the design, implementation and verification of a novel method for the optimization of the control parameters (such as step size μ and filter order N) of LMS and RLS adaptive filters used for noninvasive fetal monitoring. The optimization algorithm is driven by considering the ECG electrode positions on the maternal body surface in improving the performance of these adap...

This work is concerned with the performance of adaptive filters with both poles and zeros in active noise control (ANC) applications. This filtered-error type of applications makes it necessary to modify classical adaptive algorithms to cancel the noise. Thus, a well established theory exists for filtered-error adaptive FIR filters, with a special mention for the FxLMS algorithm. However, when ...

Adaptive filters are often involved in many applications, such as system identification, channel estimation, echo and noise cancellation in telecommunication systems. In this context, the Least Mean Square (LMS) algorithm is used to adapt a Finite Impulse Response (FIR) filter with a relatively low computation complexity and good performance. However, this solution suffers from significantly de...

To evaluate the characteristics of edge-preserving adaptive filters for selectively eliminating noise without affecting resolution in low-dose scanning, we have developed a digital phantom image and evaluated noise statistical values, noise characteristics, and resolution characteristics. The results confirmed that edge-preserving adaptive filters function as smoothing filters in low-contrast r...

This work considers the implementation of recursive identification algorithms based on hyperstability concepts with polyphase structures. It is shown that the SPR condition required for convergence of these schemes can always be met by using a sufficiently high polyphase expansion factor M . For a given M , the degree of persistent excitation required for parameter convergence is obtained. When...

In this paper, we present a novel technique for the design of FIR and IIR digital filters. The design approach begins with the specification of a discrete set of arbitrary magnitude and phase characteristics which describe a desired filter response. These frequency domain characteristics are used to create an ideal 'pseudo-filter' whose impulse response is unknown and possibly non-causal, but w...

In this paper we provide a new filtering scheme for the detection and the removal of impulsive noise in digital color images. The proposed adaptive nonlinear vector filters take the advantages of the robust order-statistic theory, generalized directional distance filter and standard sigma filter concept. The principles of the design are explained in detail. Simulation studies indicate that the ...

This paper describes an adaptive filtering approach for multichannel image processing. We present a general formulation based on rational functions (RF) and fuzzy concepts using fuzzy transformations, which allows the use of adaptive weights in the filtering structure, and we discuss different filter designs. Simulation results illustrate the strong potential of the new adaptive fuzzy filters f...

Two novel adaptive nonlinear filter structures are proposed which are based on linear combinations of order statistics. These adaptive schemes are modifications of the standard LMS algorithm and have the ability to incorporate constraints imposed on coefficients in order to permit location-invariant and unbiased estimation of a constant signal in the presence of additive white noise. The conver...

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...