Nonlinear Decomposition Method Research Articles

Formula omitted] filtering for discrete fuzzy stochastic systems with randomly occurred sensor nonlinearities

The problem of H∞ filtering for a class of discrete T–S fuzzy stochastic systems with randomly occurred sensor nonlinearities is investigated in this paper. By introducing a general sector-bounded nonlinear decomposition method and a Bernoulli random binary distribution approach, we deal with the nonlinearities and missing measurements, which are induced by the limitation of communication networks. Sufficient conditions are established to ensure that the error system is stochastically stable and has a guaranteed H∞ attenuation level. Furthermore, an explicit expression of the desired filter is also given. Two numerical results are finally employed to demonstrate the merits and applicabilities of the proposed approach.

Decomposing race and gender differences in underweight and obesity in South Africa

Using data from the National Income Dynamics Study, we document differentials in both underweight and obesity across race and gender in post-Apartheid South Africa. Using a nonlinear decomposition method, we decompose these differences across gender within race and then across race within gender. Less than one third of the differences in obesity and underweight across gender are explained by differences in covariates. In contrast, at least 70% of the obesity differences across race are explained by differences in covariates. Behavioral variables such as smoking and exercise explain the largest part of the bodyweight differentials across gender. For bodyweight differentials across race within gender, however, socioeconomic status and background variables have the largest explanatory power for obesity differentials, while background variables play the key role in explaining the underweight differentials. These results indicate that eradicating obesity and underweight differentials will require targeting policies to specific groups.

Ethnic disparities in the transition to home ownership

This paper examines ethnic disparities in the transition to home ownership using longitudinal register data from the Netherlands. The study performs a discrete duration model to account for individual and parental background and neighbourhood conditions. Subsequently, the size of explained variance in the home ownership gap between Dutch and ethnic minority groups is estimated using the Oaxaca–Fairlie non-linear decomposition method. The analysis indicates that the home ownership gap is the highest for Moroccans (0.07) of which only 0.042 is explained by the observed characteristics. For Turkish residents, 0.043 of the total 0.046 gap is explained by their background characteristics. The estimated transition rate to home ownership for Surinamese migrants would have been slightly higher than for Dutch residents if they had the same characteristics as Dutch residents. Western migrants have the smallest gap (0.024), of which 0.021 is explained by their observed characteristics.

Ethnic Disparities in the Transition to Home Ownership

This paper examines ethnic disparities in the transition to home ownership using longitudinal register data from the Netherlands. The study performs a discrete duration model to account for individual and parental background and neighbourhood conditions. Subsequently, the size of explained variance in the home ownership gap between Dutch and ethnic minority groups is estimated using the Oaxaca-Fairlie non-linear decomposition method. The analysis indicates that the home ownership gap is the highest for Moroccans (0.07) of which only 0.042 is explained by the observed characteristics. For Turkish residents, 0.043 of the total 0.046 gap is explained by their background characteristics. The estimated transition rate to home ownership for Surinamese migrants would have been slightly higher than for Dutch residents if they had the same characteristics as Dutch residents. Western migrants have the smallest gap (0.024), of which 0.021 is explained by their observed characteristics.

Medical expenditures among immigrant and nonimmigrant groups in the United States: findings from the Medical Expenditures Panel Survey (2000-2008).

The objective of the study was to examine time trends and differences in medical expenditures between noncitizens, foreign-born, and US-born citizens. We used multi-year Medical Expenditures Panel Survey (2000-2008) data on noninstitutionalized adults in the United States (N=190,965). Source specific and total medical expenditures were analyzed using regression models, bootstrap prediction techniques, and linear and nonlinear decomposition methods to evaluate the relationship between immigration status and expenditures, controlling for confounding effects. We found that the average health expenditures between 2000 and 2008 for noncitizens immigrants ($1836) were substantially lower compared with both foreign-born ($3737) and US-born citizens ($4478). Differences were maintained after controlling for confounding effects. Decomposition techniques showed that the main determinants of these differences were the availability of a usual source of health care, insurance, and ethnicity/race. Lower health care expenditures among immigrants result from disparate access to health care. The dissipation of demographic advantages among immigrants could prospectively produce higher pressures on the US health care system as immigrants age and levels of chronic conditions rise. Barring a shift in policy, the brunt of the effects could be borne by an already overextended public health care system.

Decomposıtıon of elastıc constant tensor ınto orthogonal parts

In this paper, we have elaborated on the decomposition methods such as irreducible decomposition, orthonormal tensor basis, harmonic and spectral decomposition for elastic constant tensor. Irreducible decomposition and orthonormal tensor basis methods are developed by using the results of existing theories in the literature. As examples to each decomposition method, we give results for the decomposition of elastic constant tensor in triclinic symmetry as well as materials with isotropic and transversely isotropic symmetry. Numerical examples serve to illustrate and verify each of the four decomposition methods. These examples are used to compare the decomposition methods explicitly. As a result of comparison process, it is stated that the spectral method is a non-linear invariant decomposition method that yields non-linear orthogonal parts contrary to the other three methods which are linear invariant decomposition methods. It is also shown that total scalar (isotropic) part is decomposed into two physically meaningful orthogonal parts by irreducible decomposition, orthonormal tensor basis and spectral methods. While in harmonic decomposition method, decomposition of total scalar part is not orthogonal. We propose that it is possible to make these parts orthogonal to each other. International Journal of Engineering, Science and Technology, Vol. 2, No. 6, 2010, pp. 22-46

EMPIRICAL MODE DECOMPOSITION AND CORRELATION PROPERTIES OF TRAFFIC FLUCTUATION

This work describes the application of an important tool which can extract periodic information from the time-series of fluctuating traffic data. Compared to the traditional approach using FFT techniques, the nonlinear empirical mode decomposition (EMD) method has a number of advantages. This method is adaptive and therefore highly efficient at identifying embedded structures, even those with small amplitudes. Using this analysis, the traffic time series can be completely decomposed into five temporal modes including a 24-hour cycle, a 1-week cycle and a trend. Simultaneity, long-range correlations in traffic time series are investigated by detrended fluctuation analysis (DFA). In order to accurately capture the scaling exponents, EMD analysis is performed for DFA of the traffic records. The results of DFA for the data cleaned by subtracting the first intrinsic mode functions (IMF) are apparently improved, although the DFA curves are not entirely straight on the log-log plot.

Pourquoi les immigrés portugais veulent-ils tant retourner au pays ?

The 2003 Survey on Immigrants’ Transition to Retirement helps one to understand why Portuguese residents in France express intentions to return to their home country in twice the proportion of their Spanish and Italian counterparts. Community differences in educational attainment, duration of stay , proficiency in French, location of relatives, and origin of spouse (for married respondents) explain a large share of the gaps. The application of non-linear decomposition methods reveals that differences between the characteristics chosen account for almost 70 percent of the gaps, while the differentiated effect of factors influencing the desired retirement location explains one-third.

Minding the Gap

To examine differences in Emergency Department (ED) utilization between Medicaid enrollees and the uninsured. We use nationally representative data for adults age 19-64 from the 2004 Medical Expenditure Panel Survey. We calculate descriptive statistics highlighting differences in distributions of measurable characteristics and logit regressions describing differences in the coefficients of the characteristics between the 2 groups. Blinder-Oaxaca nonlinear decomposition methods are applied to quantify the effect that differences in measurable characteristics between the groups have on the differences in ED utilization, as well as examine the magnitude of the effect on utilization of differences in behavior between the groups. Twenty-seven percent of Medicaid enrollees had an ED visit, whereas 10% of those uninsured the entire year had an ED visit. Roughly half of the utilization gap can be explained by differences in measurable characteristics. Although predisposing factors such as demographic and socioeconomic characteristics explain little of the gap, the variables capturing health limitations reflecting need explain a more substantial amount of the gap. Specifically, the higher presence of chronic conditions reported by Medicaid enrollees accounts for 18 percentage points of the gap, and reporting fair or poor health status explains 10 percentage points of the disparity. Decomposition analysis results show that differences in measurable characteristics between the groups explain half of the disparity in visits. The remaining portion of the gap in ED utilization is driven by differences in unmeasured or unobserved characteristics between the groups such as care-seeking behavioral differences.

Modified linear–nonlinear decomposition method for chaotic synchronization

This Letter proposes a general linear–nonlinear decomposition method for chaotic synchronization. The method expands the concept of chaotic synchronization based on the stability criterion of linear systems, proposed earlier. Retaining the basic idea of the standard linear–nonlinear decomposition method—the nonlinear part of a given chaotic system is used as a synchronization signal, hence the error system is always linear and allows precise stability analysis—the proposed method allows to design not only one, but a large number of coupling variants, thus offering the researcher the possibility to choose the best possible coupling variant for a given chaotic synchronization problem.

Noise reduction and data recovery for a VLF-EM survey using a nonlinear decomposition method

Geologic noise and background electromagnetic (EM) waves often degrade the quality of very low frequency electromagnetic (VLF-EM) data. To retrieve signals with significant geologic information, we used a new nonlinear decomposition technique called the empirical mode decomposition (EMD) method with the Hilbert transform. We conducted a 2D resistivity model study that included inversion of the synthetic data to test the accuracy and capabilities of this method. Next, we applied this method to real data obtained from a field experiment and a geologic example. The filtering procedure for real data starts with applying the EMD method to decompose the VLF data into a series of intrinsic mode functions that admit a well-behaved Hilbert transform. With the Hilbert transform, the intrinsic mode functions yielded a spectrogram that presents an energy-wavenumber-distance distribution of the VLF data. We then examined the decomposed data and their spectrogram to determine the noise components, which we eliminated to obtain more reliable VLF data. The EMD-filtered data and their associated spectrograms indicated the successful application of this method. Because VLF data are recorded as a complex function of the real variable distance, the in-phase and quadrature parts are complementary components of each other and could be a Hilbert transform pair if the data are analytical and noise free. Therefore, by comparing the original data set with the one obtained from the Hilbert transform, we could evaluate data quality and could even replace the original with its Hilbert transform counterpart with acceptable accuracy. By application of both this technique and conventional methods to real data in this study, we have shown the superiority of this new method and have obtained a more reliable earth model by inverting the EMD-filtered data.

11-Year solar cycle in the stratosphere extracted by the empirical mode decomposition method

We apply a novel method to extract the solar cycle signal from stratospheric data. An alternative to traditional analysis is a nonlinear empirical mode decomposition (EMD) method. This method is adaptive and therefore highly efficient at identifying embedded structures, even those with small amplitudes. Using this analysis, the geopotential height in the Northern Hemisphere can be completely decomposed into five non-stationary temporal modes including an annual cycle, a QBO signal, an ENSO-like mode, a solar cycle signal and a trend. High correlations with the sunspot cycle unambiguously establish that the fourth mode is an 11-year solar cycle signal.

Nested median filtering for detecting T-wave offset in ECGs

Capabilities of a nonlinear signal decomposition method based on nested median filters for electrocardiogram (ECG) analysis are demonstrated. This method is comparable to linear scale-space filtering in terms of computation cost but outperforms it with regard to detection accuracy of characteristic points of ECGs (e.g. the T-wave offset). Obtained results are validated on the CSE database of ECGs.

Inequalities in health: Some international comparisons

This study explores the inequality of opportunity in child malnutrition in ten developing countries in Asia, where a high proportion of children still remain vulnerable to food insecurity. This study takes account of multidimensional aspects of household and parental socio-economic status, and partitions children into distinct types through a data-driven clustering method. This is followed by a comparison of the malnutrition rates between types. Next, we decompose the observed disparity into the factors that are associated with the between-type disparity in malnutrition rates through a non-linear decomposition method. The results indicate that in all 10 countries, significant between-type disparities are found. We find the largest difference in Pakistan as 21.7 percentage points and the smallest difference in Maldives as 5.9 percentage points. In five of the ten countries, the difference in household affluence explains the largest part of the observed between-type disparity. All the results suggest that priority should be given to protecting children from marginalised households in order to mitigate the inequality in child health.