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In this research paper, we have introduced a family of adaptive filtering algorithms for noise abrogation in communication systems. There are various algorithms to find the optimal value in a digital transmission system. But among them, the evolutionary variable step size of Least Mean Square algorithm (EVSSLMS) is inspired by the “competitive methods” from the online learning literature. The predicated...
This paper analyses the effect of noisy near-field amplitude data on the phase retrieval algorithm. Additive white Gaussian noise is applied on the signal. Signal-to-noise ratios between 3 dB and 60 dB are considered. It'll be shown that using the Iterative Fourier Transform the far-field data can be obtained even under low signal-to-noise ratio.
Contour curves of shapes are important features for image analysis and understanding. A contour curve might be affected by various kinds of noise. In this paper a rapid curve denoising algorithm is proposed, which is equivalent to the existing Gaussian smoothing according to a convergence property of noise. A key problem of the rapid algorithm is to select a proper smoothing radius. We first sample...
The closeness centrality can be considered as the natural distance metric between pairs of nodes in connected graphs. This paper is the initial study of the influence of the closeness centrality of the graph built on the basis of the differential evolution dynamics to the differential evolution convergence rate. Our algorithm is based on the principle that the differential evolution creates graph...
This paper investigates the performance of iterative learning control (ILC) scheme that is adopted in networked control systems with data dropouts, where a linear discrete-time stochastic system can be rewritten as a super-vector formulation. In this paper, two types of compensation schemes are employed for data dropouts occur in both the output signals and control input signals during the signals...
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...
This paper presents a data-driven control scheme to iteratively achieve the desired objective criterion with significant improvement of the convergence performance for linear-time-invariant (LTI) single-input-single-output (SISO) systems. The internal iterative behavior between the current parameter and the optimal parameter is firstly analyzed with mathematic expression. And a novel iterative law...
We consider the problem of distributed estimation for stochastic linear systems with intermittent observations. An optimal diffusion Kalman filter has been derived by minimizing the mean-squared estimation error for each node. Convergence of the estimation error covariance is proved under some mild assumptions and an upper bound is obtained for the estimation error covariance. A critical value for...
This paper deals with an adaptive observer methodology for estimating the frequency of an unknown periodic signal with non-zero fundamental component corrupted by unstructured and bounded uncertainties. The proposed estimator is characterized by Input-to-State Stability (ISS) with respect to the bounds on the higher order harmonics and on the unstructured disturbance. The influence of each tuning...
In this paper, we investigate a decentralized formation control algorithm for an undirected formation control model. Unlike other formation control problems where only the shape of a configuration counts, we emphasize here also its Euclidean embedding. By following this decentralized formation control law, the agents will converge to certain equilibrium of the control system. In particular, we show...
In active noise control (ANC) system, the injection of white Gaussian noise (WGN) for online feedback path modeling and neutralization (FBPMN) degrades the noise-reduction-performance (NRP). In this paper: (1) a tuning free gain scheduling of WGN is used to improve the NRP of ANC system, and (2) a variable step-size is used to compensate for the decrease in the convergence of FBPMN filter due to gain...
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...
Recursive least square (RLS) is a ubiquitous adaptive filtering algorithm used in general adaptive signal processing applications. However, it is well known that RLS is sensitive to outlier contaminated in measurements. Traditional robust RLS has difficulties to cope with correlated ambient noise. To provide robustness in such cases, a robust RLS via outlier pursuit (RRLSvOP) framework is proposed...
This paper deals with active noise control (ANC) for impulsive noise sources for which the filtered-x least mean square (FxLMS) algorithm becomes unstable. By minimizing the fractional lower order moment, the resulting filtered-x least mean p-power (FxLMP) algorithm has an update vector being computed using sign operator and fractional power of the residual error signal. This results in improved robustness...
Parameter estimation plays a key role in describing a dynamical system behavior accurately. Thus, the inverse problems to identify the parameter values which characterize the dynamical system have attracted much attention from the engineering field in recent years. The Lankarani-Nikravesh (L-N) contact force model, which is proven to be more consistent with the physics of contact, is employed to describe...
Incorporation of user feedback in enterprise management products can greatly enhance our understanding of modern technology challenges and amplify the ability for those products to home in to user environments. In this paper we present an entropy-based confidence determination approach to process user feedback data (direct or indirect) to automatically rank and update the beliefs of any recommender...
The recently proposed joint-optimized normalized least-mean-square (JO-NLMS) algorithm was developed in the context of a state variable model. Moreover, following the minimization of the system misalignment and using an iterative procedure for adjusting the system model parameter, this algorithm is able to achieve a proper compromise between the performance criteria (i.e., fast convergence/tracking...
In this paper a state estimator for high tech flexible systems with an inherent nonlinearity in the output dynamics is proposed. We consider an application in which sensor measurements of the flexible system become parameter (position) dependent. An LPV setting is proposed for the design of estimators that estimate flexible modes of the system. The possibility of pole placement for the error dynamics...
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...
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