Zoran H Perić

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Numerous outcome prediction models have been developed for mortality and functional outcome after spontaneous intracerebral haemorrhage (ICH). However, no outcome prediction model for ICH has considered the impact of care restriction. To develop and compare results of the artificial neural networks (ANN) and logistic regression (LR) models, based on initial(More)
  • Milan R Dinčić, Zoran H Perić, Jelena R Lukić, Dragan B Denić
  • 2014
This paper deals with the designing of the forward adaptive μ-law companding quantizer whose levels are coded with the Golomb-Rice code. The designing is performed for measurement signals with the Gaussian distribution and applied for the speech signal. The model satisfies the G. 712 standard and achieves the decreasing of the bit-rate for 1.34 bps (bits(More)
OBJECTIVE To develop and test model to predict outcome of treatment with initial lamotrigine monotherapy in adult patients with newly diagnosed localization - related epilepsy, using data available at the time of diagnosis. METHODS Prospective longitudinal study included consecutive series of adult patients with newly diagnosed localization - related(More)
In this paper, a DPCM (Differential Pulse Code Modulation) system with forward adaptive Lloyd-Max's quantizer is presented. This quantizer is designed for low bit rate, where the first and the second order linear predictors are used in the proposed DPCM system solution. It is shown how SQNR (Signal to Quantization Noise Ratio) and G p (Prediction Gain)(More)
The motivation of this paper is based on the fact that a straightforward solution to optimization of the widely used µ-law companding quantizer has not been proposed so far. We deal with this problem for the case of a Laplacian source and we apply Muller's method for the optimization of the quantizer in question. Particularly, we use minimal distortion(More)
Speech prediction is extensively based on linear models. However, components generated by nonlinear effects are also contained in speech signals, which is neglected using linear techniques. This paper presents long-term nonlinear predictors based on second-order Volterra filters that are shown to be superior to linear long-term predictors with only a(More)
SUMMARY In this paper the piecewise uniform polar quantization of Gaussian source is analyzed. Simultaneous inside the rings after the first partition the constant probability density function of input signal vector amplitude is supposed. For this case and for the given code rate we optimized the granular distortion in order to get the manner of total(More)
In this paper simple and complete asymptotical analysis is given for a piecewise uniform product two-dimensional Laplace source quantizer (PUPTDLSQ) with respect to mean-square error (mse). PUPTDLSQ is based on uniform product two-dimensional Laplace source quantizers. Product quantizer optimality conditions and all main equation for a number of phase(More)
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