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Electrocardiogram (ECG) can help to diagnose range of diseases including heart arrhythmias, heart enlargement, heart inflammation (pericarditis or myocarditis) and coronary heart disease. ECG consists of noise which is non stationary that affects the reliability of ECG waveform. In this paper an adaptive filter for denoising ECG signal based on Least Mean Squares (LMS), Normalized Least Mean Square...
Active Noise Control (ANC) has been gaining an increasing interest in recent years. Much attention has been devoted to design of efficient control algorithms, enabling noise reduction at a high level, with computational load acceptable by currently available electronics. Among different approaches to noise control, employment of vibrating plates as secondary sources or as active barriers is particularly...
The normalized least mean pth power (NLMP) algorithm based on adaptive Volterra filters has conflicting requirement of fast convergence rate and low steady-state error. To address this problem, a novel combination of two NLMP (CNLMP) algorithms is proposed which adaptively combines two independent NLMP filters with large and small step sizes to obtain fast convergence rate and low misadjustment in...
Active Noise Canceller has become very common in modern day to day electronic equipment. The adaptive filters installed inside this canceller play a crucial role in noise cancellation. The computational complexity as well as the structural complexity of the filter is an important factor to be considered for the overall performance. This depends on the structure of the filter. The structure depends...
In this paper, a gradient based approach to adapt the parameters of the Weighted Vector Median Filter is presented. The validity of the method is inspected through a convergence test of the filter parameters and with results of noisy image filtering.
It is well known that the performance of the Constant Modulus Algorithm (CMA) for interference cancellation is limited by a so-called notch compromise. This paper presents a new recursive structure based on Godard's Criterion for blind interference suppression which overcomes this drawback. This interference-rejection structure is based on the linear prediction of the interference. The effectiveness...
In this paper, we propose a frequency domain active noise control (ANC) system without a secondary path model. The proposed system is based on the frequency domain simultaneous perturbation (FDSP) method we have proposed. In this system, the coefficients of the adaptive filter are updated only by error signals. The conventional ANC system using the filtered-x algorithm becomes unstable due to the...
Based on the adaptive filtering mode, we discussed and analyzed how to improve the quality of microphone array speech enhancement and reduce the complexity of the algorithm. This paper described a new variable step least mean square (LMS) algorithm which could reduce the effect of input noise to step factor, improve the performance of the algorithm. The algorithm smoothed the step factor in time domain...
This paper compares the performance analysis of our proposed New Time Varying LMS (NTVLMS) algorithm with other well-known adaptive algorithms such as LMS, NLMS, RVSSLMS, NVSSLMS and TVLMS algorithm. These algorithms have been tested for their adaptive noise cancellation capabilities in the context of stationary signal corrupted by additive white Gaussian noise. The parameters Convergence rate, output...
When the system model and noise statistical characteristics are known, the conventional Kalman filtering algorithm is suitable. In most cases, the noise statistics are unknown. To improve the alignment precision and convergence speed of strap-down inertial navigation system, an initial alignment method based on Sage-Husa adaptive filter is proposed. Automatic on-line estimation and correction for...
This paper first reviews an adaptation algorithm named Recursive Least Moduli (RLM) algorithm for complex-domain adaptive filters. The RLM algorithm achieves significant improvement in the filter convergence speed when the filter input is strongly correlated. Stochastic models are presented for two types of impulse noise found in adaptive filtering systems: one in observation noise and another at...
This paper proposes a memory proportionate affine projection sign algorithm (IAF-MP-APSA) by assigning an individual activation factor to each filter coefficient. In this algorithm, each individual activation factor is calculated by past and current values of the corresponding coefficient magnitude. Moreover, taking into account the memory property of the proportionate factors leads to a decrease...
The Filtered-Reference LMS, also known as FxLMS algorithm, is one of the most commonly used adaptive algorithms for noise control systems. It is appreciated due to its simplicity, low computational complexity, and performance efficiency. For its convergence, responses of the acousto-electric secondary path and its model should not differ by more than pi/2 for any frequency contributing to the noise...
This paper proposes an adaptation algorithm named Recursive Least Normalized Correlation Norms (RLNCN) algorithm for adaptive filters, based on a cost function of a quantity named Normalized Correlation Norm (NCN) which generically yields a family of normalized type algorithms. The RLNCN algorithm achieves a significant improvement in filter convergence speed, while it preserves robustness against...
This paper proposes a new adaptation algorithm named Normalized Recursive Least Moduli (NRLM) algorithm which employs “p-modulus” of error and “q-norm” of filter input. p-modulus and q-norm are generalization of the modulus and norm used in complex-domain adaptive filters. The NRLM algorithm with p-modulus and q-norm makes adaptive filters fast convergent and robust against two types of impulse noise:...
In active noise control (ANC) systems, an acoustic feedback signal may degrade the ANC performance and/or cause system instability. To solve such a problem, various online feedback path modeling (OFPM) methods using additive random noise have been reported. However, the additive random noise signal may contribute to the residual output noise. In this paper, a new random noise injection control is...
There exists noise in measurements of power signals. We studied structuring elements (SE) and their influence to denoising properties, and proposed a new denoising algorithm. The new algorithm uses the median morphological operation including the median opening-closing operation and the median closing-opening operation to improve denoising properties, and uses the cosine SE and the circle SE to make...
In many practical active noise control (ANC) applications, feedback structure using estimated secondary path to synthesize reference signal is preferred under various conditions. This paper analyzes the convergence behavior of the narrowband feedback ANC systems with imperfect secondary path estimation. Existing approaches do not include the analysis of the reference signal synthesis errors due to...
This paper first revisits least mean modulus (LMM) algorithm for complex-domain adaptive filters, presents a mathematical model for impulsive observation noise called CGN, and reviews recursive least moduli (RLM) algorithm that combines the LMM algorithm with recursive estimation of inverse covariance matrix of filter inputs. The RLM algorithm is effective in making the convergence of an adaptive...
This paper first reviews least mean modulus-Newton (LMM-Newton) algorithm that combines LMM algorithm for complex-domain adaptive filters with simple recurrent calculation of the inverse covariance matrix of the filter reference input process. The LMM-Newton algorithm is effective in improving the convergence of an adaptive filter with a strongly correlated input, while preserving the robustness of...
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