A new transmission model in cognitive radio based on cyclic generalized polynomial codes for bandwidth reduction

The frequency spectrums are inefficiently utilized and cognitive radio has been proposed for full utilization of these spectrums. The central idea of cognitive radio is to allow the secondary user to use the spectrum concurrently with the primary user with the compulsion of minimum interference. However, designing a model with minimum interference is a challenging task. In this paper, a transmission model based on cyclic generalized polynomial codes discussed in [2] and [15], is proposed for the improvement in utilization of spectrum. The proposed model assures a non interference data transmission of the primary and secondary users. Furthermore, analytical results are presented to show that the proposed model utilizes spectrum more efficiently as compared to traditional models.

Multicollinearity and financial constraint in investment decisions: a bayesian generalized ridge regression

This paper addresses the investment decisions considering the presence of financial constraints of 373 large Brazilian firms from 1997 to 2004, using panel data. A Bayesian econometric model was used considering ridge regression for multicollinearity problems among the variables in the model. Prior distributions are assumed for the parameters, classifying the model into random or fixed effects. We used a Bayesian approach to estimate the parameters, considering normal and Student t distributions for the error and assumed that the initial values for the lagged dependent variable are not fixed, but generated by a random process. The recursive predictive density criterion was used for model comparisons. Twenty models were tested and the results indicated that multicollinearity does influence the value of the estimated parameters. Controlling for capital intensity, financial constraints are found to be more important for capital-intensive firms, probably due to their lower profitability indexes, higher fixed costs and higher degree of property diversification.

Generalized interval vector spaces and interval optimization

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Zero sets of bivariate Hermite polynomials

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Para-orthogonal polynomials from constant Verblunsky coefficients

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Bounds for the zeros of symmetric kravchuk polynomials

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

Analysis of generalized interictal discharges using quantitative EEG

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

Szegö polynomials: quadrature rules on the unit circle and on [-1, 1]

We consider some of the relations that exist between real Szegö polynomials and certain para-orthogonal polynomials defined on the unit circle, which are again related to certain orthogonal polynomials on [-1, 1] through the transformation x = (z1/2+z1/2)/2. Using these relations we study the interpolatory quadrature rule based on the zeros of polynomials which are linear combinations of the orthogonal polynomials on [-1, 1]. In the case of any symmetric quadrature rule on [-1, 1], its associated quadrature rule on the unit circle is also given.

Comparative study between powers of sigmoid functions, MLP-backpropagation and polynomials in function approximation problems

Function approximation is a very important task in environments where the computation has to be based on extracting information from data samples in real world processes. So, the development of new mathematical model is a very important activity to guarantee the evolution of the function approximation area. In this sense, we will present the Polynomials Powers of Sigmoid (PPS) as a linear neural network. In this paper, we will introduce one series of practical results for the Polynomials Powers of Sigmoid, where we will show some advantages of the use of the powers of sigmiod functions in relationship the traditional MLP-Backpropagation and Polynomials in functions approximation problems.

Investigation of the cingulate cortex in idiopathic generalized epilepsy

Studies using quantitative neuroimaging have shown subtle abnormalities in patients with idiopathic generalized epilepsy (IGE). These findings have several locations, but the midline parasagittal structures are most commonly implicated. The cingulate cortex is related and may be involved. The objective of the current investigation was to perform a comprehensive analysis of the cingulate cortex using multiple quantitative structural neuroimaging techniques. Thirty-two patients (18 women, 30 ± 10 years) and 36 controls (18 women, 32 ± 11 years) were imaged by 3 Tesla magnetic resonance imaging (MRI). A volumetric three-dimensional (3D) sequence was acquired and used for this investigation. Regions-of-interest were selected and voxel-based morphometry (VBM) analyses compared the cingulate cortex of the two groups using Statistical Parametric Mapping (SPM8) and VBM8 software. Cortical analyses of the cingulate gyrus was performed using Freesurfer. Images were submitted to automatic processing using built-in routines and recommendations. Structural parameters were extracted for individual analyses, and comparisons between groups were restricted to the cingulate gyrus. Finally, shape analyses was performed on the anterior rostral, anterior caudal, posterior, and isthmus cingulate using spherical harmonic description (SPHARM). VBM analyses of cingulate gyrus showed areas of gray matter atrophy, mainly in the anterior cingulate gyrus (972 mm(3) ) and the isthmus (168 mm(3) ). Individual analyses of the cingulate cortex were similar between patients with IGE and controls. Surface-based comparisons revealed abnormalities located mainly in the posterior cingulate cortex (718.12 mm(2) ). Shape analyses demonstrated a predominance of anterior and posterior cingulate abnormalities. This study suggests that patients with IGE have structural abnormalities in the cingulate gyrus mainly localized at the anterior and posterior portions. This finding is subtle and variable among patients.

On partial derivative-Neumann's problem in generalized functions framework

In this paper, we show that the equation delta u/delta (z) over bar + Gu = f, where the elements involved are in generalized functions context, has a local solution in the generalized functions context.

Regra de Sinais de Descartes para polinômios ortogonais

Pós-graduação em Matematica Aplicada e Computacional - FCT