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1.
张家树  肖先赐 《通信学报》2001,22(10):93-98
在二阶Volterra滤波器基础上,提出了一种用于低维混沌时间自适应预测的非线性自适应预测器。基于最小均方误差准则导出了一种NLMS类型的自适应算法来实时调整这种非线性滤波预测器的系数,仿真实验结果表明:这种线性化的非线性自适应滤波预测器能够有效地预测低维混时间序列,且它的模块化特征更易于VLSI电路实现,具有广泛的工程应用价值。  相似文献   

2.
In this paper, constructive approximation theorems are given which show that under certain conditions, the standard Nadaraya-Watson (1964) regression estimate (NWRE) can be considered a specially regularized form of radial basis function networks (RBFNs). From this and another related result, we deduce that regularized RBFNs are m.s., consistent, like the NWRE for the one-step-ahead prediction of Markovian nonstationary, nonlinear autoregressive time series generated by an i.i.d. noise processes. Additionally, choosing the regularization parameter to be asymptotically optimal gives regularized RBFNs the advantage of asymptotically realizing minimum m.s. prediction error. Two update algorithms (one with augmented networks/infinite memory and the other with fixed-size networks/finite memory) are then proposed to deal with nonstationarity induced by time-varying regression functions. For the latter algorithm, tests on several phonetically balanced male and female speech samples show an average 2.2-dB improvement in the predicted signal/noise (error) ratio over corresponding adaptive linear predictors using the exponentially-weighted RLS algorithm. Further RLS filtering of the predictions from an ensemble of three such RBFNs combined with the usual autoregressive inputs increases the improvement to 4.2 dB, on average, over the linear predictors  相似文献   

3.
The linear autoregressive (AR) model is often used to investigate the pathophysiologic mechanisms controlling heart rate (HR) dynamics. This study implemented parametric models new to this field to determine if a more appropriate HR dynamics modeling structure exists. The linear AR and autoregressive-moving average (ARMA) models, and the nonlinear polynomial autoregressive (PAR) and bilinear (BL) models were fit to instantaneous HR time series obtained from nine subjects in the supine position. Model orders were determined by the Akaike Information Criteria (AIC). Model residual variance was used as the primary intermodel comparison criterion, with significance evaluated by a λ2 distributed statistic. The BL model best represented the HR dynamics, as its residual variance was significantly (p<0.05) smaller than that of the corresponding AR model for nine out of nine data sets. In all cases, the BL model had a smaller residual variance than either the ARMA or PAR models. The bilinear model was ineffective at data forecasting, however, the authors show that this cannot reflect BL model validity because poor prediction is inherent to the BL model structure. The apparent superiority of the nonlinear bilinear model suggests that future heart rate dynamics studies should put greater emphasis on nonlinear analyses  相似文献   

4.
为了准确地从遥感数据中获取城市植被覆盖度(VFC)信息,以线性混合光谱模型(LSMM)为原理基础,参考各城市端元模型,利用MODIS时间序列提取武汉研究区2007至2014年间植被覆盖度,获得植被覆盖度年际变化情况。在对遥感影像进行端元提取及确定时,结合四种城市端元模型分别对研究区植被覆盖度进行估算,并对像元分解精度作对比分析。结果表明,MODIS时间序列使用混合光谱分析法能够科学客观地实现对研究区植被覆盖度的提取,可以有效地进行周期性监测和分析研究区植被覆盖变化。  相似文献   

5.
An evolutionary structure optimisation method for the Gaussian radial basis function network is presented for modelling and predicting nonlinear time series. The generalisation performance is significantly improved with a much smaller network, compared with that of the previous clustering and least square learning method  相似文献   

6.
Detection and elimination of the shadows of moving objects in video sequences have been one of the major challenges in tracking applications. Since moving shadows cannot be removed from foreground by motion-based background subtraction methods, they lead to confusion and error in moving object tracking. In this paper, a novel classification method based on hierarchical mixture of experts learning for detecting shadows from foreground is proposed. A hierarchical mixture of MLP experts method (HMME) with semi-supervised teacher-directed learning (SSP-HMME) is used. It contains a two-level mixture of experts (ME) system. The main superiority of this method is that it is more robust than state-of-the-art methods in all types of indoor and outdoor environments. The robustness is against the number of light sources, illumination conditions, surface orientations, object sizes, etc., and it is estimated using accuracy rates. The video set has been collected from 7 different datasets. The results of experiments in outdoor and indoor environments show the validity of the method in the improvement on the accuracy of both detection and discrimination rate for moving shadows in video sequences. The results of the experiments show the accuracy rate of 89 % in average in different indoor and outdoor environmental conditions that is about 6 % better than current state-of-the-art methods.  相似文献   

7.
In this paper we extend the results on the multiple time-scale structure for linear autonomous systems of the form $$\dot x = A( \in )x$$ (cf. Coderchet al. [1]) to nonlinear autonomous systems. Our main result is in obtaining conditions under which the linearized system and the nonlinear system around an equilibrium point have the same time-scale structure.  相似文献   

8.
Smith  I. 《Electronics letters》1989,25(18):1237-1239
An improved technique is presented here for modelling the dynamic large-signal properties of microwave devices such as GaAs MESFETs. The method is based on repeated harmonic balance analysis of a simple nonlinear circuit. Many of the sources of inconsistency in established modelling methods have been avoided, making more reliable circuit analysis possible.<>  相似文献   

9.
Chen  S. 《Electronics letters》1995,31(2):117-118
An improved clustering and recursive least squares (RLS) learning algorithm for Gaussian radial basis function (RBF) networks is described for modelling and predicting nonlinear time series. Significant performance gain can be achieved with a much smaller network compared with the usual clustering and RLS method  相似文献   

10.
A discrete time domain modelling is presented for the pulse-width modulated series resonant converter (PWM-SRC) with a discontinuous current mode. This nonlinear system is linearized about its equilibrium state to obtain a linear discrete time model for the investigation of small signal performances such as the stability and transient response. The usefulness of this small signal model is verified by dynamic simulation.  相似文献   

11.
Correlation functions of continuous-time periodically correlated processes can be represented by a Fourier series with coefficient functions. It is shown that the usual estimator for stationary covariances, formed from a single sample path of the process, can be simply modified to provide a consistent (in quadratic mean) estimator for any of the coefficient functions resulting from the aforementioned representation. It is shown that, if the process is Gaussian and B k(τ) is a Fourier integral with respect to a density function gk(λ), a two-dimensional periodogram, formed from a single sample function, can be smoothed along a line of constant difference frequency to provide a consistent estimator for gk(λ). This natural extension of the well-known procedure for stationary processes provides a method for nonparametric spectral analysis of periodically correlated processes  相似文献   

12.
Learning graphical models for stationary time series   总被引:1,自引:0,他引:1  
Probabilistic graphical models can be extended to time series by considering probabilistic dependencies between entire time series. For stationary Gaussian time series, the graphical model semantics can be expressed naturally in the frequency domain, leading to interesting families of structured time series models that are complementary to families defined in the time domain. In this paper, we present an algorithm to learn the structure from data for directed graphical models for stationary Gaussian time series. We describe an algorithm for efficient forecasting for stationary Gaussian time series whose spectral densities factorize in a graphical model. We also explore the relationships between graphical model structure and sparsity, comparing and contrasting the notions of sparsity in the time domain and the frequency domain. Finally, we show how to make use of Mercer kernels in this setting, allowing our ideas to be extended to nonlinear models.  相似文献   

13.
Gaps in time series can produce spurious features in power spectrum estimates. These artifacts can be suppressed by averaging spectrum estimates obtained by first windowing the time series with a collection of orthogonal tapers. Such multitaper methods have been used for data without gaps since the early 1980s and for more general sampling schemes since the late 1980s. We introduce three families of tapers for time series with gaps. Two of the families solve optimization problems. They minimize bounds on different measures of bias. Computing them involves solving large eigenvalue problems with special structure that can be exploited to construct efficient algorithms. The third family solves no particular optimization problem but is inexpensive to compute and gives spectrum estimates that are quite similar to the other two for actual and simulated helioseismic data. All three families of gap-adapted multitaper estimates have lower variance and bias than the periodogram. In simulations of helioseismic data with gaps, standard methods for constructing confidence intervals for multitaper spectrum estimates, including parametric approximations and resampling in the temporal and spectral domains, all failed to attain their nominal confidence level. We present a novel resampling technique that, in the same simulations, gave confidence intervals that attained the correct confidence level.  相似文献   

14.
一种新颖的混沌时间序列分析方法   总被引:1,自引:0,他引:1  
本文提出了一种新颖的混沌时间序列分析方法,即从被加性高斯白噪声污染的混沌时间序列中估计其系统参数并同时进行噪声抑制的方法。假定产生混沌时间序列的模型已知,但相应的参数未知。这种新方法把对混沌时间序列的参数估计和噪声抑制看作是一种最小化过程,并利用了最速梯度下降方法解决。数值模拟实验表明新方法要优于现有的方法,是估计混沌系统系数和噪声抑制的一种有效的方法。  相似文献   

15.
16.
《Signal processing》1986,10(2):129-144
The number of axis-crossings properly normalized tends to land on or near the dominant frequency of a mixed spectrum. Such dominancy can be achieved by linear filtering. This observation is proved useful in the fast detection of isolated sinusoidal components. The method is applied successfully to some well-known data sets.  相似文献   

17.
An accurate numerical method for calculating nonlinear electrostatic discharges is presented. The method represents an improvement over the FDTD scheme in that it includes the arc model of Rompe and Weizel [1944]. Numerical results that demonstrate the validity and accuracy of the model are presented  相似文献   

18.
A new generic modified Saleh (MS) model for use in memoryless nonlinear power amplifier (PA) behavioural modelling is proposed. The model was evolved primarily to overcome some particular weaknesses in the original Saleh model when handling the polar AM-PM envelope modelling. From it new twoparameter MS polar models are derived. By modelling a nearmemoryless LDMOS PA amplifying a WCDMA signal, evidence of the improvement in modelling accuracy and performance of the MS over the original Saleh for both polar and quadrature models is provided.  相似文献   

19.
This paper describes analytical advances and practical experiences in a nonlinear controller design methodology for series resonant DC/DC converters. The control goal is to maintain the output voltage (which is the only measured variable) in the presence of large-load perturbations by varying the switching frequency. The proposed methodology utilizes large-scale, nonlinear switched, and generalized averaged models, and the resulting closed-loop system is exponentially convergent under typical operating conditions. The designer has a direct handle over the convergence rate, and the nonlinear controller requires only the usual output voltage measurements, while the load variations are estimated. The control structure allows for variations in both resistive and current loads. The dissipativity-based nonlinear controller is implemented in affordable analog circuitry and evaluated experimentally  相似文献   

20.
Basic statistics of a nonstationary time series are estimated from its single realization. The estimates are represented in the form of a recurrent procedure forming residual time series and smoothing them with the help of effective models of digital data filtering or a locally weighted polynomial regression. The concept of local time weighting and robust weighting of residual series is generalized on the basis of a rational combination of models of distance-weighted least squares and an exponentially weighted regression. The estimation of trends, volatility, and autocorrelation for time series of companies’ sales volumes and the price dynamics of stock assets is simulated, and the results of simulation are presented.  相似文献   

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