Wiener System identification using B-spline functions with De Boor recursion

A simple and effective algorithm is introduced for the system identification of Wiener system based on the observational input/output data. The B-spline neural network is used to approximate the nonlinear static function in the Wiener system. We incorporate the Gauss-Newton algorithm with De Boor algorithm (both curve and the first order derivatives) for the parameter estimation of the Wiener model, together with the use of a parameter initialization scheme. The efficacy of the proposed approach is demonstrated using an illustrative example.

System identification of Wiener systems with B-spline functions using De Boor recursion

In this article a simple and effective algorithm is introduced for the system identification of the Wiener system using observational input/output data. The nonlinear static function in the Wiener system is modelled using a B-spline neural network. The Gauss–Newton algorithm is combined with De Boor algorithm (both curve and the first order derivatives) for the parameter estimation of the Wiener model, together with the use of a parameter initialisation scheme. Numerical examples are utilised to demonstrate the efficacy of the proposed approach.

Digital predistorter design using B-Spline neural network and inverse of De Boor algorithm

This contribution introduces a new digital predistorter to compensate serious distortions caused by memory high power amplifiers (HPAs) which exhibit output saturation characteristics. The proposed design is based on direct learning using a data-driven B-spline Wiener system modeling approach. The nonlinear HPA with memory is first identified based on the B-spline neural network model using the Gauss-Newton algorithm, which incorporates the efficient De Boor algorithm with both B-spline curve and first derivative recursions. The estimated Wiener HPA model is then used to design the Hammerstein predistorter. In particular, the inverse of the amplitude distortion of the HPA's static nonlinearity can be calculated effectively using the Newton-Raphson formula based on the inverse of De Boor algorithm. A major advantage of this approach is that both the Wiener HPA identification and the Hammerstein predistorter inverse can be achieved very efficiently and accurately. Simulation results obtained are presented to demonstrate the effectiveness of this novel digital predistorter design.

Complex-valued B-spline neural networks for modeling and inverting Hammerstein systems

Many communication signal processing applications involve modelling and inverting complex-valued (CV) Hammerstein systems. We develops a new CV B-spline neural network approach for efficient identification of the CV Hammerstein system and effective inversion of the estimated CV Hammerstein model. Specifically, the CV nonlinear static function in the Hammerstein system is represented using the tensor product from two univariate B-spline neural networks. An efficient alternating least squares estimation method is adopted for identifying the CV linear dynamic model’s coefficients and the CV B-spline neural network’s weights, which yields the closed-form solutions for both the linear dynamic model’s coefficients and the B-spline neural network’s weights, and this estimation process is guaranteed to converge very fast to a unique minimum solution. Furthermore, an accurate inversion of the CV Hammerstein system can readily be obtained using the estimated model. In particular, the inversion of the CV nonlinear static function in the Hammerstein system can be calculated effectively using a Gaussian-Newton algorithm, which naturally incorporates the efficient De Boor algorithm with both the B-spline curve and first order derivative recursions. The effectiveness of our approach is demonstrated using the application to equalisation of Hammerstein channels.

Random regression analyses using B-spline functions to model growth of Nellore cattle

The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.

Use of glass transition temperature for stabilization of board's cracks of Eucalyptus grandis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Study of the thermal behavior of the transition phase of Co(II)-diclofenac compound by non-isothermal method

The Co(II)-diclofenac complex was evaluated by simultaneous thermogravimetry-differential thermal analysis (TG-DTA) and differential scanning calorimetry (DSC). The DTA curve profile shows one exothermic peak because of the transition phase of the compound between 170 and 180 A degrees C, which was confirmed by X-ray powder diffractometry. The transition phase behavior was studied by DSC curves at several heating rates of a sample mass between 1 and 10 mg in nitrogen atmosphere and in a crucible with and without a lid. Thus, the kinetic parameters were evaluated using an isoconversional non-linear fitting proposed by Capela and Ribeiro. The results show that the activation energy and pre-exponential factor for the transition phase is dependant on the different experimental conditions. Nevertheless, these results indicate that the kinetic compensation effect shows a relationship between them.

Combination of nickel and titanium complexes containing nitrogen ligands as catalyst for polyethylene reactor blending

Ethylene was polymerized using a combination of Ni(diimine)Cl-2 (1) (diimine = 1,4-bis(2,6-di-isopropylphenyl)-acenaphthenediimine) and {Tp(Ms)*} TiCl3 (2) (Tp(Ms)* = hydridobis(3-mesitylpyrazol-1-yl)(5-mesityl-pyrazol-1-yl)) compounds in the presence of methyl-aluminoxane (MAO) at 30 degrees C. The productivity reaches a maximum at X-Ni = 0.75 (1400 kg of PE/mol[M] . h), and the produced polyethylene (PE) showed maximal melt flow index (0.13 g/10 min) and minimal intrinsic viscosity (2.24 dL/g) compared to polyethylenes obtained with different values of nickel loading fractions (X-Ni). Productivity intrinsic viscosity data, as well as melt flow index measurements markedly depend upon the content of the late transition metal, thus suggesting a synergic effect between nickel and titanium catalysts.

Critical exponents for a transition from integrability to non-integrability via localization of invariant tori in the Hamiltonian system

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Anomalous metamagnetic-like transition in a FeRh/Fe3Pt interface occurring at T approximate to 120 K in the field-cooled-cooling curves for low magnetic fields

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Exercise training in the aerobic/anaerobic metabolic transition prevents glucose intolerance in alloxan-treated rats

Background: Ninety percent of cases of diabetes are of the slowly evolving non-insulin-dependent type, or Type 2 diabetes. Lack of exercise is regarded as one of the main causes of this disorder. In this study we analyzed the effects of physical exercise on glucose homeostasis in adult rats with type 2 diabetes induced by a neonatal injection of alloxan. Methods: Female Wistar rats aged 6 days were injected with either 250 mg/ kg of body weight of alloxan or citrate buffer 0.01 M (controls). After weaning, half of the animals in each group were subjected to physical training adjusted to meet the aerobic-anaerobic metabolic transition by swimming 1 h/day for 5 days a week with weight overloads. The necessary overload used was set and periodically readjusted for each rat through effort tests based on the maximal lactate steady state procedure. When aged 28, 60, 90, and 120 days, the rats underwent glucose tolerance tests (GTT) and their peripheral insulin sensitivity was evaluated using the HOMA index. Results: The area under the serum glucose curve obtained through GTT was always higher in alloxan-treated animals than in controls. A decrease in this area was observed in trained alloxan-treated rats at 90 and 120 days old compared with non-trained animals. At 90 days old the trained controls showed lower HOMA indices than the non-trained controls. Conclusion: Neonatal administration of alloxan induced a persistent glucose intolerance in all injected rats, which was successfully counteracted by physical training in the aerobic/anaerobic metabolic transition. © 2008 Mota et al; licensee BioMed Central Ltd.

Random regression analyses using B-spline functions to model growth of Nellore cattle

The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.

Construction of polynomial spline spaces over quadtree and octree T-meshes

[EN]We present a new strategy for constructing tensor product spline spaces over quadtree and octree T-meshes. The proposed technique includes some simple rules for inferring local knot vectors to define spline blending functions. These rules allow to obtain for a given T-mesh a set of cubic spline functions that span a space with nice properties: it can reproduce cubic polynomials, the functions are C2-continuous, linearly independent, and spaces spanned by nested T-meshes are also nested. In order to span spaces with these properties applying the proposed rules, the T-mesh should fulfill the only requirement of being a 0-balanced quadtree or octree. ..

A simple strategy for defining polynomial spline spaces over hierarchical T-meses

[EN]We present a new strategy for constructing spline spaces over hierarchical T-meshes with quad- and octree subdivision scheme. The proposed technique includes some simple rules for inferring local knot vectors to define C 2 -continuous cubic tensor product spline blending functions. Our conjecture is that these rules allow to obtain, for a given T-mesh, a set of linearly independent spline functions with the property that spaces spanned by nested T-meshes are also nested, and therefore, the functions can reproduce cubic polynomials. In order to span spaces with these properties applying the proposed rules, the T-mesh should fulfill the only requirement of being a 0- balanced mesh...

Construction of polynomial spline spaces over quadtree and octree T-meshes

[EN]We present a new strategy for constructing tensor product spline spaces over quadtree and octree T-meshes. The proposed technique includes some simple rules for inferring local knot vectors to define spline blending functions. These rules allow to obtain for a given T-mesh a set of cubic spline functions that span a space with nice properties: it can reproduce cubic polynomials, the functions are C2-continuous, linearly independent, and spaces spanned by nested T-meshes are also nested. In order to span spaces with these properties applying the proposed rules, the T-mesh should fulfill the only requirement of being a 0-balanced quadtree or octree. ..