Developing a mathematical model for the artificial generation of electrocardiogram (ECG) signals is a subject that has been widely investigated. One of its uses is for the assessment of diagnostic ECG signal processing devices. So the model should have the capability of producing a wide range of ECG signals, with all the nuances that reflect the sickness to which humans are prone, and this ...

Objective- To evaluate the role of greater omentum incorporation of coral in healing of the long bone defect in dog model. Design- Experimental in-vivo study. Animals- Sixteen adult mongrel male dogs weighing 26.2±2.5 kg, free of evident infectious or parasitic illnesses were used in this study. Procedures- The operative procedure was undertaken under general anesthesia. Radial bone was expo...

Radial and elliptic flow in noncentral heavy-ion collisions can constrain the effective equation of state (EOS) of the excited nuclear matter. To this end, a model combining relativistic hydrodynamics and a hadronic transport code [Sorge, Phys. Rev. C 52, 3291 (1995)] is developed. For an EOS with a first-order phase transition, the model reproduces both the radial and elliptic flow data at the...

Abstract. In order to describe large transverse momentum (pT ) distributions observed in high energy nucleus-nucleus collisions, a stochastic model in the three dimensional rapidity space is introduced. The fundamental solution of the radial symmetric diffusion equation is Gaussianlike in radial rapidity. We can also derive a pT or radial rapidity distribution function, where a distribution of ...

In this paper, a comparison study is presented on artificial intelligence and time series models in 1-hour-ahead wind speed forecasting. Three types of typical neural networks, namely adaptive linear element, multilayer perceptrons, and radial basis function, and ARMA time series model are investigated. The wind speed data used are the hourly mean wind speed data collected at Binalood site in I...

In this paper we focus on an interpretation of Gaussian radial basis functions (GRBF) which motivates extensions and learning strategies. Specifically, we show that GRBF regression equations naturally result from representing the input-output joint probability density function by a finite mixture of Gaussians. Corollaries of this interpretation are: some special forms of GRBF representations ca...

Complexity-penalization strategies are one way to decide on the most appropriate network size in order to address the trade-off between overfitted and underfitted models. In this paper we propose a new penalty term derived from the behaviour of candidate models under noisy conditions that seems to be much more robust against catastrophic overfitting errors that standard techniques. This strateg...

Spotting tasks require detection of target patterns from a background of richly varied non-target inputs. The performance measure of interest for these tasks, called the figure of merit (FOM), is the detection rate for target patterns when the false alarm rate is in an acceptable range. A new approach to training spotters is presented which computes the FOM gradient for each input pattern and t...