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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.
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   

3.
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   

4.
This paper deals with the privacy-preserving average consensus problem for continuous-time multi-agent network systems (MANSs) based on the event-triggered strategy. A novel event-triggered privacy-preserving consensus algorithm is designed to achieve the average consensus of MANSs while avoiding the disclosure of the agents’ initial states. Different from the approaches incorporating stochastic noises, an output mask function in the proposed algorithm is developed to make initial state of each agent indiscernible by the others. Particularly, under the output mask function, all agents can exactly tend to the average value of initial states rather than the mean square value. Under the proposed algorithm, detailed theoretical proof about average consensus and privacy of the MANSs are conducted. Moreover, the proposed algorithm is extended to nonlinear continuous-time MANSs, and the corresponding results are also derived. A numerical simulation eventually is performed to demonstrate the validity of our results.  相似文献   

5.
The conventional logarithm cost-based adaptive filters, e.g., the least mean logarithmic square (LMLS) algorithm, cannot combat impulsive noises at the filtering process. To address this issue, we present a novel robust least mean logarithmic square (RLMLS) algorithm by using a generalized logarithmic cost function. The proposed RLMLS algorithm can provide robustness against impulsive noises with the improvement of filtering accuracy. For theoretical analysis, the mean square analysis of RLMLS is provided in terms of the mean square deviation (MSD) and excess mean-square error (EMSE) with a white Gaussian reference. For further performance improvement in different noises, the variable step-size RLMLS (VSSRLMLS) based on the statistics of error is proposed to improve the convergence rate and steady-state mean square error, simultaneously. Analytical results and superiorities of RLMLS and VSSRLMLS in the context of system identification are supported by simulations from the aspects of filtering accuracy and robustness in Gaussian and impulse noises.  相似文献   

6.
This study presents a novel frequency synchronization scheme for orthogonal frequency division multiple access uplink systems. The proposed approach first estimates the carrier frequency offset (CFO) from the zeros of a backward prediction system. Then, based on the CFO estimates, two types of filters, namely zero-forcing and the linearly constrained minimum variance filters, are developed to suppress multiple access interference (MAI). Computer simulation results show that in addition to having a reduced computational complexity, the proposed algorithm has reliable CFO estimates and possesses at least a 3-dB power gain in MAI suppression over conventional minimum mean square error algorithms for frequency synchronization.  相似文献   

7.
This paper is concerned with the robust state estimation problem for semi-Markovian switching complex-valued neural networks with quantization effects (QEs). The uncertain parameters are described by the linear fractional uncertainties (LFUs). To enhance the channel utilization and save the communication resources, the measured output is quantized before transmission by a logarithmic quantizer. The purpose of the problem under consideration is to design a full-order state estimator to estimate the complex-valued neuron states. Based on the Lyapunov stability theory, stochastic analysis method, and some improved integral inequalities, sufficient conditions are first derived to guarantee the estimation error system to be globally asymptotically stable in the mean square. Then, the desired state estimator can be directly designed after solving a set of matrix inequalities, which is robust against the LFUs and the QEs. In the end of the paper, one numerical example is provided to illustrate the feasibility and effectiveness of the proposed estimation design scheme.  相似文献   

8.
This paper is concerned with the quantitative mean square exponential stability and stabilization for stochastic systems with Markovian switching. First, the concept of quantitative mean square exponential stability(QMSES) is introduced, and two stability criteria are derived. Then, based on an auxiliary definition of general finite-time mean square stability(GFTMSS), the relations among QMSES, GFTMSS and finite time stochastic stability (FTSS) are obtained. Subsequently, QMSE-stabilization is investigated and several new sufficient conditions for the existence of the state and observer-based controllers are provided by means of linear matrix inequalities. An algorithm is given to achieve the relation between the minimum states’ upper bound and the states’ decay velocity. Finally, a numerical example is utilized to show the merit of the proposed results.  相似文献   

9.
A novel finite-time complex-valued zeroing neural network (FTCVZNN) for solving time-varying Sylvester equation is proposed and investigated. Asymptotic stability analysis of this network is examined with any general activation function satisfying a condition or with an odd monotonically increasing activation function. So far, finite-time model studies have been investigated for the upper bound time of convergence using a linear activation function with design formula for the derivative of the error or with variations of sign-bi-power activation functions to zeroing neural networks. A function adaptive coefficient for sign-bi-power activation function (FA-CSBP) is introduced and examined for faster convergence. An upper bound on convergence time is derived with the two components in the function adaptive coefficients of sign-bi-power activation function. Numerical simulation results demonstrate that the FTCVZNN with function adaptive coefficient for sign-bi-power activation function is faster than applying a sign-bi-power activation function to the zeroing neural network (ZNN) and the other finite-time complex-valued models for the selected example problems.  相似文献   

10.
This paper proposes a passive fuzzy controller design methodology for nonlinear system with multiplicative noises. Applying the Itô's formula and the sense of mean square, the sufficient conditions are developed to analyze the stability and to design the controller for stochastic nonlinear systems which are represented by the Takagi-Sugeno (T-S) fuzzy models. The sufficient conditions derived in this paper belong to the Linear Matrix Inequality (LMI) forms which can be solved by the convex optimal programming algorithm. Besides, the passivity theory is applied to discuss the effect of external disturbance on system. Finally, some numerical simulation examples are provided to demonstrate the applications of the proposed fuzzy controller design technique.  相似文献   

11.
The magnitude-squared coherence (MSC) is a measure that estimates the extent to which one real- or complex-valued signal can be predicted from another real- or complex-valued signal using a linear model. It is also used as a measure of the similarities in the frequency content of two signals. The measure is widely used in signal analysis, especially in fields such as biomedical, where a large number of signals must be processed simultaneously. It is natural to wish to generalize this idea to compare two vector-valued signals, and a variety of approaches have been proposed. This paper reviews these generalizations, presents new relationships among the measures, and demonstrates a series of results that show the similarities and dissimilarities among these measures. Some of the measures have a clear link with total interdependence; some are related to the mutual information rate. Basic results such as the various Sandwich Theorems show how the measures relate, and understanding these properties is key to an informed use of any vector generalization of MSC.  相似文献   

12.
A more general trajectory tracking and disturbance rejection problem for the random linear system is considered in this paper. The known structural properties of the reference and the disturbance signals motivate us to use the internal model principle, and the motion decomposition for the linear systems prompts us to utilize the superposition principle. Combining the spectral analysis method with the pole assignment algorithm, the stability and tracking property can be obtained. The simulation result demonstrates that all the closed-loop system is exponentially practically stable in the mean square (EpS-2-M), the tracking error can be regulated to an arbitrarily small constant by turning the parameters.  相似文献   

13.
This paper solves the problem of adaptive neural dynamic surface control (DSC) for a class of full state constrained stochastic nonlinear systems with unmodeled dynamics. The concept of the state constraints in probability is first proposed and applied to the stability analysis of the system. The full state constrained stochastic nonlinear system is transformed to the system without state constraints through a nonlinear mapping. The unmodeled dynamics is dealt with by introducing a dynamic signal and the adaptive neural dynamic surface control method is explored for the transformed system. It is proved that all signals of the closed-loop system are bounded in probability and the error signals are semi-globally uniformly ultimately bounded(SGUUB) in mean square or the sense of four-moment. At the same time, the full state constraints are not violated in probability. The validity of the proposed control scheme is demonstrated through the simulation examples.  相似文献   

14.
A problem of stabilization about uncertain networked control systems (NCSs) with random but bounded delays is discussed in this paper. By using augmented state-space method, this class of problems can be modeled as discrete-time jump linear systems governed by finite-state Markov chains. A new switched model based on probability is proposed to research problems of reliable control when actuators become ageing or partially disabled. Using improved V-K iteration algorithm, a class of reliable controllers are designed to make systems asymptotically mean square stable under several stochastic disturbances such as random time-delay and stochastic actuator failure and the maximal redundancy degree is given through this method.  相似文献   

15.
This work investigates the improved stability conditions for linear systems with time-varying delays via various augmented approaches. Some augmented approaches are augmented Lyapunov-Krasovskii functionals, augmented zero equalities, and the augmented zero equality approach. At first, by constructing augmented Lyapunov-Krasovskii functionals including the state vectors which were not considered in the previous works and augmented zero equalities, a stability criterion is proposed in the forms of linear matrix inequalities. Through the proposed Lyapunov-Krasovskii functionals and an additional functional derived from the integral inequality, a slightly improved result is derived. The proposed results do not consider the increase in the computational complexity to achieve a larger delay bound. So, by applying the augmented zero equality approach, which is a method of grafting the proposed augmented zero equality proposed in Finsler Lemma, to the proposed result, an enhanced stability result was derived. Also, the computational complexity is reduced by appropriately adjusting any vector of the integral inequality utilized in the proposed criteria. By applying some numerical examples to the proposed conditions, the effectiveness and superiority of the results are confirmed.  相似文献   

16.
This paper studies the fault-tolerant model-free adaptive control (FT-MFAC) problem for a class of single-input single-output (SISO) nonlinear networked control systems (NCSs) under denial-of-service (DoS) attacks. A novel FT-MFAC framework is established with the consideration of DoS attacks and the sensor fault, in which DoS attacks obeying the Bernoulli distribution randomly happen in the sensor-to-controller channel and the sensor fault is approximated by the radial basis function neural network (RBFNN). Based on the proposed framework, an FT-MFAC algorithm that uses only input/output data is proposed to guarantee that the output tracking error is bounded in the sense of mean square. Finally, the effectiveness of the proposed algorithm is illustrated by a simulation.  相似文献   

17.
自适应滤波算法根据采用优化准则的不同,通常分为两类最基本算法:最小均方误差(LMS)类算法和递归最小二乘(RLS)类算法。本文重点介绍了最小均方误差算法和递归最小二乘算法,并将这两类算法在MATLAB上进行仿真,并对结果作出比较和分析。  相似文献   

18.
In the paper, a control algorithm for output regulation problem of nonlinear pure-feedback systems with unknown functions is proposed. The main contributions of the proposed method are not only to avoid Assumptions of unknown functions, but also adopt a non-backstepping control scheme. First, a high-gain state observer with disturbance signals is designed based on the new system that has been converted. Second, an internal model with the observer state is established. Finally, based on Lyapunov analysis and the neural network approximation theory, the control algorithm is proposed to ensure that all the signals of the closed-loop system are the semi-globally uniformly ultimately bounded, and the tracking error converges to a small neighborhood of the origin. Three simulation studies are worked out to show the effectiveness of the proposed approach.  相似文献   

19.
王辉  陈水福  唐锦春 《科技通报》2006,22(5):661-665,670
采用数值模拟方法预测建筑风载及风环境时,计算区域的边界及界面离散的方法将直接影响风场解的收敛和准确性。基于结构化同位网格在建筑风场模拟中的应用,并结合控制容积法的离散及压力校正算法的实施,提出了合理的计算边界,且相应给出了压力校正方程的界面离散方法。经算例分析,上述方法不仅能保证迭代收敛并取得较为准确的风场解,而且实现了同一计算网格能适用于不同风向的模拟,提高了正交结构化网格的适用性。  相似文献   

20.
在数字通信中,接收信号通常会受到码间干扰的影响,尤其是在多径衰弱无线信道环境中,这种现象更为严重。采用盲均衡技术可以消除码间干扰。针对基于常数模算法的判决反馈盲均衡收敛速度慢,稳态误差大的缺点,提出了一种新的多模判决反馈盲均衡算法。算法用信号的独立模值取代常数模算法的模值,加快了收敛速度减小了稳态误差。通过计算法仿真对两种算法进行比较,仿真结果证明了新算法的有效性。  相似文献   

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