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1.
Recently, the augmented complex-valued normalized subband adaptive filtering (ACNSAF) algorithm has been proposed to process colored non-circular signals. However, its performance will deteriorate severely under impulsive noise interference. To overcome this issue, a robust augmented complex-valued normalized M-estimate subband adaptive filtering (ACNMSAF) algorithm is proposed, which is obtained by modifying the subband constraints of the ACNSAF algorithm using the complex-valued modified Huber (MH) function and is derived based on CR calculus and Lagrange multipliers. In order to improve both the convergence speed and steady-state accuracy of the fixed step size ACNMSAF algorithm, a variable step size (VSS) strategy based on the minimum mean squared deviation (MSD) criterion is devised, which allocates individual adaptive step size to each subband, fully exploiting the structural advantages of SAF and significantly improving the convergence performance of the ACNMSAF algorithm as well as its tracking capability in non-stationary environment. Then, the stability, transient and steady-state MSD performance of the ACNMSAF algorithm in the presence of colored non-circular inputs and impulsive noise are analyzed, and the stability conditions, transient and steady-state MSD formulas are also derived. Computer simulations in impulsive noise environments verify the accuracy of theoretical analysis results and the effectiveness of the proposed algorithms compared to other existing complex-valued adaptive algorithms.  相似文献   

2.
The fast affine projection (FAP) algorithm (Gay and Tavathia, Proceedings of the IEEE International Conference on Acoustic, Speech and Signal Processing, 1995, 3023) is known to outperform the NLMS with a slight increase in complexity, but it involves the fast calculation of the inverse of a covariance matrix of the input data that could undermine the performance of the algorithm. The block subband adaptive algorithm in (Courville and Duhamel, IEEE Trans. Signal Processing 46(9) (1998) 2359) has also illustrated significant improvement in performance over the NLMS and other frequency domain adaptive algorithms. However, it is known that block processing algorithms have lower tracking capabilities than the their sample-by-sample counterparts. In this paper, we present a sample-by-sample version of the algorithm in (Courville and Duhamel, IEEE Trans. Signal Processing 46(9) (1998) 2359) and develop a low complexity implementation of this algorithm. As a sample-by-sample algorithm, it avoids the reduced tracking capability of block algorithms. Because it does not use matrix inversion, it avoids the numerical problems of FAP algorithms. We will show that the new sample-by-sample algorithm approximates the affine projection algorithm and possesses a similar property in reducing coefficient bias that appears in monophonic and stereophonic teleconferencing when the receiving room impulse responses are undermodeled. The new fast sample-by-sample algorithm is extended for stereo acoustic echo cancellation. Simulations of echo cancellations in actual rooms are presented to verify our findings.  相似文献   

3.
《Journal of The Franklin Institute》2022,359(17):10172-10205
Recently, the sparsity-aware sign subband adaptive filter algorithm with individual-weighting-factors (S-IWF-SSAF) was devised. To accomplish performance enhancement, the variable parameter S-IWF-SSAF (VP-S-IWF-SSAF) algorithm was developed through optimizing the step-size and penalty factor, respectively. Different from the optimization scheme, we devise a family of variable step-size strategy S-IWF-SSAF (VSS-S-IWF-SSAF) algorithms based on the transient model of algorithms via minimizing the mean-square deviation (MSD) on each iteration with some reasonable and frequently adopted assumptions and Price's theorem. And in order to enhance the tracking capability, an effective reset mechanism is also incorporated into the proposed algorithms. It is worth mentioning that the presented algorithms could acquire lower computational requirements and exhibit higher steady-state estimation accuracy obviously and acceptable tracking characteristic in comparison to the VP-S-IWF-SSAF algorithm. In addition, the stable step-size range in the mean and mean square sense and steady-state performance are concluded. And the computational requirements are exhibited as well. Monte-Carlo simulations for system identification and adaptive echo cancellation applications certify the proposed algorithms acquire superior performance in contrast to other related algorithms within various system inputs under impulsive interference environments.  相似文献   

4.
This article proposes an affine-projection-like maximum correntropy (APLMC) algorithm for robust adaptive filtering. The proposed APLMC algorithm is derived by using the objective function based on the maximum correntropy criterion (MCC), which can availably suppress the bad effects of impulsive noise on filter weight updates. But the overall performance of the APLMC algorithm may be decreased when the input signal is polluted by noise. To compensate for the deviation of the APLMC algorithm in the input noise interference environment, the bias compensation (BC) method is introduced. Therefore, the bias-compensated APLMC (BC-APLMC) algorithm is presented. Besides, the convergence of the BC-APLMC algorithm in the mean and the mean square sense is studied, which provides a constraint range for the step-size. Computer simulation results show that the APLMC, and BC-APLMC algorithms are valid in acoustic echo cancellation and system identification applications. It also shows that the proposed algorithms are robust in the presence of input noise and impulse noise.  相似文献   

5.
In this paper, we propose an adapt-then-combine (ATC) diffusion normalized Huber adaptive filtering (ATC-DNHuber) algorithm for distributed estimation in impulsive interference environments. Firstly, a normalized Huber adaptive filter (NHuber) is developed to reduce the effect of the eigenvalue spread of the input signal. Then we extend the NHuber to develop an ATC diffusion algorithm by applying the NHuber algorithm at all agents. In addition, the mean stability performance and computational complexity are analyzed theoretically. In addition, Furthermore, simulation results demonstrate that the ATC-DNHuber algorithm can perform better in identifying the unknown coefficients under the complex and changeable impulsive interference environments.  相似文献   

6.
A full performance analysis of complex normalized subband adaptive filter (CNSAF) algorithm will provide guidelines for designing the adaptive filter. However, because of the noncircular characteristic of complex-value signal, the complementary mean-square performance analysis of the CNSAF algorithm has not been presented in the literature. In order to give the detailed theoretical expressions of the CNSAF algorithm, the present study first analyzes the mean-square deviation (MSD) with the energy-conservation method, and then the complementary mean-square derivation (CMSD) behavior is given using pseudo-energy-conservation method. Analytical expressions are obtained for the transient MSD and CMSD of the CNSAF algorithm. Also, the steady-state MSD and CMSD are predicted based on the closed-form expressions. Besides, the analysis results are not constrained by the distribution of input signals. Finally, simulation results obtained for diffferent inputs present a good consistence with the analytical results.  相似文献   

7.
In this paper, a novel augmented complex-valued normalized subband adaptive filter (ACNSAF) algorithm is proposed for processing the noncircular complex-valued signals. Based on the augmented statistics, the proposed algorithm is derived by computing a constraint cost function. Due to contain all second-order statistical properties, the ACNSAF algorithm can process the circular and noncircular complex-valued signals simultaneously. Moreover, the stability and mean square steady-state analysis of the proposed algorithm is derived by using the energy conservation principle. Computer simulation experiments on complex-valued system identification, prediction and noise cancelling show that the proposed algorithm achieves the improved mean square deviation and prediction gain compared to the ACNLMS algorithm. And the simulation results are consistent with the analysis results.  相似文献   

8.
In general feedback cancellation setups, standard adaptive filtering techniques fail to provide a reliable feedback path estimate if the desired signal is spectrally colored because of the presence of a closed signal loop. In this paper, several approaches for improving the estimation accuracy of the adaptive feedback canceller in hearing aids will be reviewed, including constrained adaptation and bandlimited adaptation of the feedback canceller as well as adaptation with the prediction-error method (PEM) using a fixed or adaptive model of the desired signal. Partitioned-block frequency-domain implementations of these algorithms will be compared for acoustic feedback paths measured in two commercial behind-the-ear hearing aids. In addition, it is shown that the tracking performance of the PEM-based feedback canceller with adaptive signal model can be improved by the so-called shadow filter approach known from echo cancellation.  相似文献   

9.
The conjugate gradient (CG) method exhibits fast convergence speed than the steepest descent, which has received considerable attention. In this work, we propose two CG-based methods for nonlinear active noise control (NLANC). The proposed filtered-s Bessel CG (FsBCG)-I algorithm implements the functional link artificial neural network (FLANN) as a controller, and it is derived from the Matérn kernel to achieve enhanced performance in various environments. On the basis of the FsBCG-I algorithm, we further develop the FsBCG-II algorithm, which utilizes the Bessel function of the first kind to constrain outliers. As an alternative, the FsBCG-II algorithm has reduced computational complexity and similar performance as compared to the FsBCG-I algorithm. Moreover, the convergence property of the algorithms is analyzed. The proposed algorithms are compared with some highly cited previous works. Extensive simulation results demonstrate that the proposed algorithms can achieve robust performance when the noise source is impulsive, Gaussian, logistic, and time-varying.  相似文献   

10.
The performance of the current state estimation will degrade in the existence of slow-varying noise statistics. To solve the aforementioned issues, an improved strong tracking maximum correntropy criterion variational-Bayesian adaptive Kalman filter is presented in this paper. First of all, the inverse-Wishart distribution, as the conjugate-prior, is adopted to model the unknown and time-varying measurement and process noise covariances, then the noise covariances and system state are estimated via the variational Bayesian method. Secondly, the multiple fading-factors are obtained and evaluated to modify the prediction error covariance matrix to address the problems associated with inaccurate error estimation. Finally, the maximum correntropy criterion is employed to correct the filtering gain, which improves the filtering performance of the proposed algorithm. Simulation results show that the proposed filter exhibits better accuracy and convergence performance compared to other existing algorithms.  相似文献   

11.
In this paper, a novel fast attitude adaptive fault-tolerant control (FTC) scheme based on adaptive neural network and command filter is presented for the hypersonic reentry vehicles (HRV) with complex uncertainties which contain parameter uncertainties, un-modeled dynamics, actuator faults, and external disturbances. To improve the performance of closed-loop FTC, command filter and neural network are introduced to reconstruct system nonlinearities that are related to complex uncertainties. Compared with the FTC scheme with only neural network, the FTC scheme with command filter and neural network has fewer controller design parameters so that the computational complexity is decreased and the control efficiency is improved, which is of great significance for HRV. Then, the adaptive backstepping fault-tolerant controller based on command filter and neural network is designed, which can solve the complexity explosion problem in the standard backstepping control and the small uncertainty problem in the backstepping control only containing command filter. Moreover, to improve the approximation accuracy of the neural network-based universal approximator, an adaptive update law of neural network weights is designed by using the convex optimization technique. It is proved that the presented FTC scheme can ensure that the closed-loop control system is stable and the tracking errors are convergent. Finally, simulation results are carried out to verify the superiority and effectiveness of the presented FTC scheme.  相似文献   

12.
Dynamic path planning for mobile robots is an urgent issue that needs to be solved because of the growing use of mobile robots in daily life and industrial operations. This work focuses on avoiding moving obstacles in dynamic situations. The computational effort required by some current algorithms makes them difficult to utilize for path planning in dynamic situations whilst the computational effort required by other methods makes them simple yet prone to local minima. In this paper, an improved simulated annealing (SA) algorithm for dynamic path planning is proposed. To reduce its computational effort, the initial path selection method and deletion operation are introduced. Simulation results show the improved SA algorithm outperforms other algorithms and provides optimal solutions in static and dynamic environments.  相似文献   

13.
提出了一种基于迭代自适应机制的改进算法,有效地缩减了分层置信传播算法(HBP)的计算时间.传统HBP计算时间随指定的迭代上限增加而线性增长.为此引入消息收敛的条件判断,在迭代上限相同情况下,减少算法的迭代次数,缩减整体迭代时间.实验表明,与传统HBP相比,该方法计算时间缩减了38％以上,计算时间对整体迭代上限不敏感.该方法可以应用于使用HBP算法的其他方法.  相似文献   

14.
In a multimodal, system, the growth in the number of possible modal paths makes state estimation difficult. Practical algorithms bound complexity by merging estimates that are conditioned on different modal path fragments. Commonly, the weight given to these local estimates is inversely related to the normalized magnitude of the residuals generated by each local filter. This paper presents a novel dual-sensor estimator that uses a merging formula that is based upon a different function of the residuals. Its performance is contrasted with an estimator using a single sensor and with another dual-sensor algorithm that requires fewer on-line calculations.  相似文献   

15.
用改进威胁模型规划后的电势理论划出实用的三维航迹.对有地形威胁和雷达、火力威胁的各种情况进行了分类、分析,并推出计算公式.通过限定搜索范围为包含起始点和目标点之间的矩形区域,不但减少了计算的复杂度,而且保证飞行路线收敛于目标点.用坡度限制平滑算法和用曲率限制平滑算法对上述航迹的法向加速度和曲率进行约束,得到符合飞行器机动性的飞行路线.  相似文献   

16.
This paper proposes anti-oscillation and chaos control scheme for the fractional-order brushless DC motor system wherein there exist unknown dynamics, immeasurable states and chaotic oscillation. Aimed at immeasurable states, the high-gain observers with fast convergence are presented to obtain the information of system states. To compensate uncertainties existing in the dynamic system, a finite-time echo state network with a weight is proposed to approximate uncertain dynamics while its weight is tuned by a fractional-order adaptive law online. Meanwhile a fractional-order filter is introduced to deal with the repeated derivative of the backstepping. Based on the fractional-order Lyapunov stability criterion, the anti-oscillation and chaos control scheme integrated with a high-gain observer, an echo state network and a filter are proposed by using recursive steps of backstepping. The proposed scheme guarantees the boundedness of all signals of the closed-loop system in the sense of global asymptotic stability, and also suppresses chaotic oscillation. Finally, the effectiveness of our scheme is demonstrated by simulation results.  相似文献   

17.
In this paper a population based evolutionary optimization methodology called Opposition based Harmony Search Algorithm (OHS) is applied for the optimization of system coefficients of adaptive infinite impulse response (IIR) system identification problem. The original Harmony Search (HS) algorithm is chosen as the parent one and opposition based approach is applied to it with an intention to exhibit accelerated near global convergence profile. During the initialization, for choosing the randomly generated population/solution opposite solutions are also considered and the fitter one is selected as apriori guess for having faster convergence profile. Each solution in Harmony Memory (HM) is generated on the basis of memory consideration rule, a pitch adjustment rule and a re-initialization process which gives the optimum result corresponding to the least error fitness in multidimensional search space. Incorporation of different control parameters in basic HS algorithm results in balancing of exploration and exploitation of search space. The proposed OHS based system identification approach has alleviated from inherent drawbacks of premature convergence and stagnation, unlike Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE). The simulation results obtained for some well known benchmark examples justify the efficacy of the proposed OHS based system identification approach over GA, PSO and DE in terms of convergence speed, identifying the system plant coefficients and mean square error (MSE) fitness values produced for both same order and reduced order models of adaptive IIR filters.  相似文献   

18.
In this paper, based on the Smith iteration (Smith, 1968), an inner-outer (IO) iteration algorithm for solving the coupled Lyapunov matrix equations (CLMEs) is presented. First, the IO iteration algorithm for solving the Sylvester matrix equation is proposed, and its convergence is analyzed in detail. Second, the IO iteration algorithm for solving the CLMEs is constructed. By utilizing the latest estimation, a current-estimation-based and two weighted IO iteration algorithms are also given for solving the CLMEs, respectively. Convergence analyses indicate that the iteration solutions generated by these algorithms always converge to the unique solutions to the CLMEs for any initial conditions. Finally, Several numerical examples are provided to show the superiority of the proposed numerical algorithms.  相似文献   

19.
本文提出一种新的基于α稳定分布噪声环境下的自适应滤波算法,这种算法针对变步长自适应滤波算法收敛速度和稳态误差相矛盾的不足,建立了步长μ(n)与误差信号e(n)之间的新的非线性函数关系。该函数能够削弱输入端不相关α稳定分布噪声对步长调整的影响,更好地解决稳态误差与收敛时间之间的矛盾。通过系统辨识仿真结果表明,新的算法α对稳定分布下的尖峰脉冲噪声有较强的韧性,比传统的NLMP算法有更快的参数辨识速度和更小的稳态误差,同时还具有很好地跟踪多时变系统的能力。  相似文献   

20.
《Journal of The Franklin Institute》2022,359(17):10145-10171
Considering the colored noises from the process environments, the parameter estimation problems for the feedback nonlinear equation-error systems interfered by moving average noises are addressed in this paper. Due to small computational burden, the gradient search principle is adopted to the feedback nonlinear systems and an overall extended stochastic gradient algorithm is derived for parameter estimation. Introducing the innovation length, the scalar innovation is expanded into the innovation vector and a multi-innovation extended stochastic gradient algorithm is further developed to reach the high estimation accuracy by utilizing more dynamical observed data. Furthermore, to assure the convergence of the proposed algorithms, their convergence properties are analyzed through the stochastic process theory. Finally, the experimental results indicate the effectiveness of the proposed algorithms.  相似文献   

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