This paper studies the parameter estimation problems of the nonlinear systems described by the bilinear state space models in the presence of disturbances.A bilinear state observer is designed for deriving identificat...This paper studies the parameter estimation problems of the nonlinear systems described by the bilinear state space models in the presence of disturbances.A bilinear state observer is designed for deriving identification algorithms to estimate the state variables using the input-output data.Based on the bilinear state observer,a novel gradient iterative algorithm is derived for estimating the parameters of the bilinear systems by means of the continuous mixed p-norm cost function.The gain at each iterative step adapts to the data quality so that the algorithm has good robustness to the noise disturbance.Furthermore,to improve the performance of the proposed algorithm,a dynamicmoving window is designed which can update the dynamical data by removing the oldest data and adding the newestmeasurement data.A numerical example of identification of bilinear systems is presented to validate the theoretical analysis.展开更多
An integrated framework is presented to represent and classify process data for on-line identifying abnormal operating conditions. It is based on pattern recognition principles and consists of a feature extraction ste...An integrated framework is presented to represent and classify process data for on-line identifying abnormal operating conditions. It is based on pattern recognition principles and consists of a feature extraction step, by which wavelet transform and principal component analysis are used to capture the inherent characteristics from process measurements, followed by a similarity assessment step using hidden Markov model (HMM) for pattern comparison. In most previous cases, a fixed-length moving window was employed to track dynamic data, and often failed to capture enough information for each fault and sometimes even deteriorated the diagnostic performance. A variable moving window, the length of which is modified with time, is introduced in this paper and case studies on the Tennessee Eastman process illustrate the potential of the proposed method.展开更多
Transition zone or ecotone is a unique community sandwiched between two communities/ecosystems/biomes.These ecotones in Himalaya remained unexplored for many ecological aspects like biodiversity,phyto-sociology,bounda...Transition zone or ecotone is a unique community sandwiched between two communities/ecosystems/biomes.These ecotones in Himalaya remained unexplored for many ecological aspects like biodiversity,phyto-sociology,boundary detection and even impact of change in land use pattern(anthropogenic activity).The most accepted and widespread technique called as Moving Split Window(MSW) technique is used for detection of vegetation and environmental boundaries at four different sites in the lesser stratum of north-west Himalaya.All the four sites were at different distances from the nearest human inhabited area.Anthropogenic activities like grazing,herb collection,wood collection etc.were common at proximal sites.Such activities have led to the change in land use pattern.In this study,we have tried to work out the impact of the change in land use pattern(human interference) on the vegetation and basic environmental parameters like soil pH,electrical conductivity and moisture on forestgrassland ecotone in north-west Himalaya.Data on mountain steepness was also collected and analyzed.The dissimilarity profile using the statistical tool Squared Euclidian Distance(SED) indicated that species turnover locations increase with the increase in distance of ecotones from human settlements.The ecotones at distant locations from human villages are characterized with blunt as well as sharp peaks for vegetation data,however,conditions are reverse in case of the proximal sites.The study also reveals that as the distance between the ecotone and human settlements increases,the complex conditions like multiple vegetation boundaries prevails on the transitions.In this regard,land use induced blurring of forest-grassland transition in north-west Himalaya is summed up in the study.展开更多
The urban-rural integrated area in Sanshui District of Foshan City was selected for research, and the impact of landscape pattern around the No.269 provincial highway was analyzed based on the land-use data in 2014 us...The urban-rural integrated area in Sanshui District of Foshan City was selected for research, and the impact of landscape pattern around the No.269 provincial highway was analyzed based on the land-use data in 2014 using the spatial analysis in GIS and the moving window method. The results showed that:(1) within the scope of a 2 km-range buffer zone, with a low degree of heterogeneity, land for construction use and water area were the dominant land-use types, while with a high degree of fragmentation, cultivated land, wooded land, grassland, garden land, land for other farm uses, and land unused were scattered;(2) the 250-m square moving window could well detect the change characteristics of landscape pattern on both sides of the road;(3) the gradient analysis of landscape pattern in urban-rural integrated area, which was conducted with the aid of a 750-m transect on both sides of the road, indicated that there were significant differences between landscape indexes both in the urban-rural integrated area and on both sides of the road;(4) the road that had an obvious cutting and fragmentation impact on the landscape was an important factor leading to the increasing fragmentation and heterogeneity to regional landscapes.展开更多
Partial least squares discriminant analysis (PLS-DA) with integrated moving-window (MW) waveband screening was applied to the discriminant analysis of liquor brands with near-infrared (NIR) spectroscopy. Luzhou Laojia...Partial least squares discriminant analysis (PLS-DA) with integrated moving-window (MW) waveband screening was applied to the discriminant analysis of liquor brands with near-infrared (NIR) spectroscopy. Luzhou Laojiao, a popular liquor with strong fragrant flavor, was used as the identified liquor brand (160 samples, negative, 52 vol alcoholicity). Liquors of 10 other brands with strong fragrant flavor were used as the interferential brands (200 samples, positive, 52 vol alcoholicity). The Kennard-Stone algorithm was used for the division of modeling samples to achieve uniformity and representativeness. Based on the MW-PLS-DA, a simplified optimal model set with 157 wavebands was further proposed. This set contained five types of wavebands corresponding to the NIR absorption bands of water, ethanol, and other micronutrients (i.e., acids, aldehydes, phenols, and aromatic compounds) in liquor for practical choice. Using five selected simple models with 4775 - 4239, 7804 - 6569, 6264 - 5844, 9435 - 7896, and 12066 - 10373 cm-1, the validation recognition rates were obtained as 99.3% or higher. Results show good prediction performance and low model complexity, and also provided a valuable reference for designing small dedicated instruments. The proposed method is a promising tool for large-scale inspection of liquor food safety.展开更多
The pricing of moving window Asian option with an early exercise feature is considered a challenging problem in option pricing. The computational challenge lies in the unknown optimal exercise strategy and in the high...The pricing of moving window Asian option with an early exercise feature is considered a challenging problem in option pricing. The computational challenge lies in the unknown optimal exercise strategy and in the high dimensionality required for approximating the early exercise boundary. We use sparse grid basis functions in the Least Squares Monte Carlo approach to solve this “curse of dimensionality” problem. The resulting algorithm provides a general and convergent method for pricing moving window Asian options. The sparse grid technique presented in this paper can be generalized to pricing other high-dimensional, early-exercisable derivatives.展开更多
In this paper, a new method for discovering the candidate car license plate locations is presented. First, the image is decomposed using a Haar wavelet to get the HL band with vertical edges. Then, the HL band image i...In this paper, a new method for discovering the candidate car license plate locations is presented. First, the image is decomposed using a Haar wavelet to get the HL band with vertical edges. Then, the HL band image is binarized using an Otsu threshold. Next a black top-hat algorithm is applied to reduce the effects of interfering large continuous features other than the license plate. At this time, a moving window based modified variance score calculation is made for areas with white pixels. This work found that the top 3 detected rectangle windows correctly locate the license plate regions with a success rate of about 98.2%. Moreover, the proposed method is robust enough to locate the plates in cases where the rough vehicle position has not been previously discovered and the cars are not centered in the image.展开更多
基金funded by the National Natural Science Foundation of China(No.61773182)the 111 Project(B12018).
文摘This paper studies the parameter estimation problems of the nonlinear systems described by the bilinear state space models in the presence of disturbances.A bilinear state observer is designed for deriving identification algorithms to estimate the state variables using the input-output data.Based on the bilinear state observer,a novel gradient iterative algorithm is derived for estimating the parameters of the bilinear systems by means of the continuous mixed p-norm cost function.The gain at each iterative step adapts to the data quality so that the algorithm has good robustness to the noise disturbance.Furthermore,to improve the performance of the proposed algorithm,a dynamicmoving window is designed which can update the dynamical data by removing the oldest data and adding the newestmeasurement data.A numerical example of identification of bilinear systems is presented to validate the theoretical analysis.
基金Supported by National Science Fund for Distinguished Young Scholars(60625302)National Key Fundamental Research Project of China(2002CB3122000)National High Technology Research and Development Program of China(863 Program)(20060104Z1081)
基金Supported by National High-Tech Program of China (No. 2001AA413110).
文摘An integrated framework is presented to represent and classify process data for on-line identifying abnormal operating conditions. It is based on pattern recognition principles and consists of a feature extraction step, by which wavelet transform and principal component analysis are used to capture the inherent characteristics from process measurements, followed by a similarity assessment step using hidden Markov model (HMM) for pattern comparison. In most previous cases, a fixed-length moving window was employed to track dynamic data, and often failed to capture enough information for each fault and sometimes even deteriorated the diagnostic performance. A variable moving window, the length of which is modified with time, is introduced in this paper and case studies on the Tennessee Eastman process illustrate the potential of the proposed method.
文摘Transition zone or ecotone is a unique community sandwiched between two communities/ecosystems/biomes.These ecotones in Himalaya remained unexplored for many ecological aspects like biodiversity,phyto-sociology,boundary detection and even impact of change in land use pattern(anthropogenic activity).The most accepted and widespread technique called as Moving Split Window(MSW) technique is used for detection of vegetation and environmental boundaries at four different sites in the lesser stratum of north-west Himalaya.All the four sites were at different distances from the nearest human inhabited area.Anthropogenic activities like grazing,herb collection,wood collection etc.were common at proximal sites.Such activities have led to the change in land use pattern.In this study,we have tried to work out the impact of the change in land use pattern(human interference) on the vegetation and basic environmental parameters like soil pH,electrical conductivity and moisture on forestgrassland ecotone in north-west Himalaya.Data on mountain steepness was also collected and analyzed.The dissimilarity profile using the statistical tool Squared Euclidian Distance(SED) indicated that species turnover locations increase with the increase in distance of ecotones from human settlements.The ecotones at distant locations from human villages are characterized with blunt as well as sharp peaks for vegetation data,however,conditions are reverse in case of the proximal sites.The study also reveals that as the distance between the ecotone and human settlements increases,the complex conditions like multiple vegetation boundaries prevails on the transitions.In this regard,land use induced blurring of forest-grassland transition in north-west Himalaya is summed up in the study.
基金Sponsored by National Natural Science Foundation of China(41671160)
文摘The urban-rural integrated area in Sanshui District of Foshan City was selected for research, and the impact of landscape pattern around the No.269 provincial highway was analyzed based on the land-use data in 2014 using the spatial analysis in GIS and the moving window method. The results showed that:(1) within the scope of a 2 km-range buffer zone, with a low degree of heterogeneity, land for construction use and water area were the dominant land-use types, while with a high degree of fragmentation, cultivated land, wooded land, grassland, garden land, land for other farm uses, and land unused were scattered;(2) the 250-m square moving window could well detect the change characteristics of landscape pattern on both sides of the road;(3) the gradient analysis of landscape pattern in urban-rural integrated area, which was conducted with the aid of a 750-m transect on both sides of the road, indicated that there were significant differences between landscape indexes both in the urban-rural integrated area and on both sides of the road;(4) the road that had an obvious cutting and fragmentation impact on the landscape was an important factor leading to the increasing fragmentation and heterogeneity to regional landscapes.
文摘Partial least squares discriminant analysis (PLS-DA) with integrated moving-window (MW) waveband screening was applied to the discriminant analysis of liquor brands with near-infrared (NIR) spectroscopy. Luzhou Laojiao, a popular liquor with strong fragrant flavor, was used as the identified liquor brand (160 samples, negative, 52 vol alcoholicity). Liquors of 10 other brands with strong fragrant flavor were used as the interferential brands (200 samples, positive, 52 vol alcoholicity). The Kennard-Stone algorithm was used for the division of modeling samples to achieve uniformity and representativeness. Based on the MW-PLS-DA, a simplified optimal model set with 157 wavebands was further proposed. This set contained five types of wavebands corresponding to the NIR absorption bands of water, ethanol, and other micronutrients (i.e., acids, aldehydes, phenols, and aromatic compounds) in liquor for practical choice. Using five selected simple models with 4775 - 4239, 7804 - 6569, 6264 - 5844, 9435 - 7896, and 12066 - 10373 cm-1, the validation recognition rates were obtained as 99.3% or higher. Results show good prediction performance and low model complexity, and also provided a valuable reference for designing small dedicated instruments. The proposed method is a promising tool for large-scale inspection of liquor food safety.
文摘The pricing of moving window Asian option with an early exercise feature is considered a challenging problem in option pricing. The computational challenge lies in the unknown optimal exercise strategy and in the high dimensionality required for approximating the early exercise boundary. We use sparse grid basis functions in the Least Squares Monte Carlo approach to solve this “curse of dimensionality” problem. The resulting algorithm provides a general and convergent method for pricing moving window Asian options. The sparse grid technique presented in this paper can be generalized to pricing other high-dimensional, early-exercisable derivatives.
文摘In this paper, a new method for discovering the candidate car license plate locations is presented. First, the image is decomposed using a Haar wavelet to get the HL band with vertical edges. Then, the HL band image is binarized using an Otsu threshold. Next a black top-hat algorithm is applied to reduce the effects of interfering large continuous features other than the license plate. At this time, a moving window based modified variance score calculation is made for areas with white pixels. This work found that the top 3 detected rectangle windows correctly locate the license plate regions with a success rate of about 98.2%. Moreover, the proposed method is robust enough to locate the plates in cases where the rough vehicle position has not been previously discovered and the cars are not centered in the image.
