In this paper, we propose a quasi-periodic parallel WaveGAN (QPPWG) waveform generative model, which applies (QP) structure to (PWG) model using pitch-dependent dilated convolution networks (PDCNNs). PWG is small-footprint GAN-based raw whose generation time much faster than real because of its compact and non-autoregressive (non-AR) non-causal mechanisms. Although achieves high-fidelity speech...

In the study, we discussed the generalized autoregressive conditional heteroskedasticity model and enhanced it with wavelet transform to evaluate the daily returns for 1/4/2002-30/12/2011 period in Brent oil market. We proposed discrete wavelet transform generalized autoregressive conditional heteroskedasticity model to increase the forecasting performance of the generalized autoregressive cond...

Certaines manifestations cutanees sont fre­quement rencontrees au cours du diabete sucre.  L'auteur decrit les lesions cutanees pro­pres au dia.bete e.: celles qui sc manifestent dans des syndromes associes au diabe:e. Bien que ces signes cutanes ne soient pas pathogno­moniques du diabete sucre, mais par leur acce­cibilite aux yeux du clinicien et par leur fre­quence ils peuvent faire penser a...

background: it is introduced that unintentional childhood poisoning can be as result of child home environment and characteristics of parents. this study aimed at quantifying the adjusted population attributable risk percentage of risk factor of unintentional childhood poisoning.  materials and methods: the hospital based case- control included 140 consecutive poisoned children who admitted to ...

The application of neural networks to non-linear dynamic system identification tasks has a long history, which consists mostly autoregressive approaches. Autoregression, the usage model outputs previous time steps, is method transferring state between not necessary for modeling systems with modern network structures, such as gated recurrent units (GRUs) and Temporal Convolutional Networks (TCNs...

Normal residual is one of the usual assumptions of autoregressive models but in practice sometimes we are faced with non-negative residuals case. In this paper we consider some autoregressive models with non-negative residuals as competing models and we have derived the maximum likelihood estimators of parameters based on the modified approach and EM algorithm for the competing models. Also,...

INTRODUCTION A polymorphism (-14 A/T) affecting PAR1 expression on the platelet surface has recently been identified. A two-fold variation in receptor density, which correlated with the platelet response to PAR1-activating peptide (PAR1-AP), has been reported. MATERIALS AND METHODS We used flow cytometry to measure the correlation between the number of PAR1 receptors and platelet activation. ...

The variational autoregressive network is extended to the Euclidean path integral representation of quantum partition function. An essential challenge adapting sequential process sample generation by an a nonlocal constraint due periodic boundary condition in integral. add-on oracle devised for this purpose, which accurately identifies and stalls unviable configurations as soon they occur. enab...

We introduce the new time series analysis features of scikits.statsmodels. This includes descriptive statistics, statistical tests and several linear model classes, autoregressive, AR, autoregressive moving-average, ARMA, and vector autoregressive models VAR.