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Recently proposed Hard Thresholding based Adaptive Filtering (HTAF) algorithm provides an on-line counterpart of a compressed sensing based greedy sparse recovery algorithm called iterative hard thresholding (IHT) by constructing a sliding-window based cost function. This leads to an adaptive algorithm with data reuse gradient term (i.e. with multi-regressors) followed by a fixed hard thresholding...
An Affine Projection algorithm (APA) with decomposed weight vector and variable step size is proposed in this paper so as to improve the performance of adaptive filter. The optimal value of variable step size is obtained by the largest decrease in the mean square deviation error. This proposed variable step size optimally decomposed APA has improved convergence with smaller value of steady state error...
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...
An acoustic noise cancellation is an approach used for reduction of additive noise in the speech signal. Normalized Least Mean Square (NLMS) algorithm is the most popular adaptive filter algorithm for noise cancellation. But in NLMS algorithm, selection of step size and filter length of adaptive filter for different type of noise with different noise level (dB) that gives maximum SNR is difficult...
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 well-known two-dimensional least-mean-square (LMS) adaptive filter has been widely used in many applications. However, it suffers from slow convergence for correlated input signals. To address this problem, this paper introduces the normalized subband adaptive filter (NSAF) into two-dimensional adaptive filtering and then develops a two-dimensional subband adaptive filter (TD-SAF). Moreover, in...
Online system identification method provides useful insight into the electromechanical plant behavior during commissioning phase as well as health monitoring. In addition to controller tuning, the methods can be applied for identifying un-modelled mechanical resonances, sensor vibrations, bearing friction, etc. Accordingly, this paper focuses on the implementation and evaluation of real time frequency...
This paper presents a cost-effective adaptive feedback Active Noise Control (FANC) method for controlling functional Magnetic Resonance Imaging (fMRI) acoustic noise by decomposing it into dominant periodic components and residual random components. Periodicity of fMRI acoustic noise is exploited by using linear prediction (LP) filtering to achieve signal decomposition. A hybrid combination of adaptive...
Gradient adaptive step size adaptive filters have been widely used to adapt different biomedical application environments and obtain useful life signals from serious ambient noise and interferences. In order to further improve the signal-to-noise ratio (SNR) of the life signals, this paper presents a class of signed-gradient adaptive step size least mean square (LMS) adaptive filters. The proposed...
This paper proposes a proportionate affine projection algorithm based on coefficient difference (DPAPA). Its adaptation gain for each tap is proportional to the absolute value of the difference between the current tap weight estimate and the previous tap weight estimate. In addition, a simple version is introduced to decrease the amount of calculation. The simulation results show that the proposed...
In this paper, a new complex adaptive notch filters using the oscillator based algorithm has been proposed. The approach presented for second-order real coefficient IIR filters has been applied to derive a coefficient-update algorithm for a first-order complex adaptive notch filter. Convergence characteristics of the proposed algorithm have been analyzed. Unbiased frequency estimation of a complex...
The traditional decision feedback equalizer embedded digital phase-locked loop (DPLL) only equalize single-channel received signal, in order to improve the performance of underwater acoustic communication, a spatial-equalization algorithm embedded DPLL is researched in this paper. Such algorithm proposed in this paper combines time gain from equalization process and space gain from spatial diversity...
By studying the shortage of the traditional fixed step size least mean square (LMS) algorithm. This paper builds a nonlinear function relationship between μ and the error signal by reviewing the existing algorithm and presents a novel variable step size LMS adaptive filtering algorithm by improving Sigmoid function based on translation transformation. The selective of parameters and the performance...
Acoustic feedback suppression is a key task of digital hearing aid which commonly uses least mean square (LMS) or normalized LMS(NLMS) adaptive algorithm to cancel acoustic feedback signal, however the characteristic of acoustic feedback signal is not considered in these algorithms. In order to improve the listening recognition of hearing-impaired patients, this paper proposes a new variable step-size...
The stability and performance of the normalized subband adaptive filter (NSAF) algorithm is influenced by the regularization parameter. However, in various noise environments, the regularization parameter is difficult to be determined. The basic idea of this paper is to eliminate the effects of the noise in filter estimation. Simulation results show the proposed method has valid results in various...
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...
In real applications, the overall active control system is nonlinear and the performance of noise cancellation is decreased by the extent of nonlinearities, so an active control system compensating nonlinear distortions is needed. In this paper, a robust multi-channel active noise controller is proposed to effectively linearize nonlinear distortions in the secondary path and be applied for actively...
Sparse system identification problems often exist in many applications, such as echo interference cancellation, sparse channel estimation, and adaptive beamforming. One of popular adaptive sparse system identification (ASSI) methods is adopting only one sparse least mean square (LMS) filter. However, the adoption of only one sparse LMS filter cannot simultaneously achieve fast convergence speed and...
De-noising magnetic resonance images (MRI) has recently become an interesting topic in medical diagnosis applications. Many algorithms have been proposed for this purpose. However, these algorithms usually suffer from poor performance or time consumption. In this paper, we propose a 2-D version of the recently proposed convex recursive inverse (RI) algorithm that provides fast convergence at the beginning...
<?Pub Dtl?>This paper presents a precise analysis of the critical path of the least-mean-square (LMS) adaptive filter for deriving its architectures for high-speed and low-complexity implementation. It is shown that the direct-form LMS adaptive filter has nearly the same critical path as its transpose-form counterpart, but provides much faster convergence and lower register complexity. From...
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