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In this communication the use of AR modelling in the estimation of cubic phase coupling is studied. After obtaining the trispectrum of an harmonic signal with cubic phase couplings, the parametric modelling is used to design a method that models this trispectrum and allows the locatation of the cubic couplings. This method is based on a twofold AR modelling of the data using their fourth-order cumulants,...
An inverse method is developed to recover for unknown stochastic inputs. The proposed approach relies on an approximate finite impulse response model of the system which is seen as a linearization around the current input estimation. The inversion itself is done within the frequency domain in order to lower the computation cost. This classical approach requires a regularization technique to be used...
A model-based fault management system for a Three Mass Torsion Oscillator is described. Fault management includes fault detection, fault diagnosis and fault compensation. A process model of system dynamics is derived. Friction effects are modelled by a neuro-fuzzy Local Linear Model Tree (LOLIMOT) approach. Parameter estimation is obtained with two simple experiments. A friction estimation stage is...
Researchers have proposed that the reliability of software prediction models can be assessed by the following most widely used evaluation criterion, i.e., Difference Measure and Ratio Measure. Ratio measure is more suitable for the assessment of the accuracy in software cost estimation. Results in this research demonstrated that applying proposed method to the software effort estimation is by far...
In this paper, we propose a technique to decrease computational times for solving static elevator operation problems which are formalized as trip-based integer linear programming models. The technique is comprised of two parts: (i) to give equations which constrain the search space on the assumption that the maximum waiting time over passengers of an optimal solution is known, and (ii) to estimate...
In this paper, we propose two new information criteria to select the desired model order for probability density function (PDF) estimation using the maximum entropy method (MEM). These two proposed information criteria are based on Akaike information criterion (AIC) and Bayesian information criterion (BIC), respectively. The PDF estimation using MEM can be presented using integer and fractional moments...
This paper describes some of the key features of the Persistent Scatterer Interferometry chain of the Geomatics (PSIG) Division of CTTC. The paper firstly provides an overview of the entire PSI chain. It then focuses on the first part of the chain, which provides the input data for the estimation of the Atmospheric Phase Screen (APS). In this part, the so-called Cousin Persistent Scatterers (CPSs)...
As an important image processing technique, image interpolation has wide applications, such as digital photos, video communication, medical imaging, object identification. A new adaptive image amplification technique is presented in this paper. The proposed method is able to cope with arbitrary integer multiples image amplification. For a low-resolution (LR) image and a given integer magnification...
Discontinuous systems have been increasingly paid attention since it can be found in various physical and biological systems. In this paper we consider an effective estimation algorithm for system with multiple discontinuities. We propose that a discontinuous-right-hand-side of state equation is approximated as multiplication of known discontinuous basis function and parameter that evolves in time...
This paper describes a novel idea for designing a fuzzy-neural network for modeling of nonlinear system dynamics. The presented approach assumes a state-space representation in order to obtain a more compact form of the model, without statement of a great number of parameters needed to represent a nonlinear behavior. To increase the flexibility of the network, simple Takagi-Sugeno inferences are used...
The paper presents a consistent and unbiased estimator for dynamic, one-step-ahead prediction of the aggregate response of a large number of individual loads to a common price signal, using only aggregate past response data. The price per unit of consumption is an exogenous signal which is updated at discrete time intervals. It is assumed that individual loads arrive in the system at random times...
This paper develops an efficient approach to analytical learning of Asymmetric Stochastic Volatility (ASV) models through nonlinear filtering, and shows that they are useful for practical risk management. This involves the derivation of a Nonlinear Quadrature Filter (NQF) that operates directly on the nonlinear ASV model. The NQF filter makes Gaussian approximations to the prior and posterior density...
This paper presents a new method for two dimensional (2-D) autoregressive (AR) model parameters estimation. Based on Levinson-Durbin method, a new approach is extended for 2-D series, and for this purpose, an algorithm is presented. The presented method preserves in the 2-D case advantages of Levinson-Durbin such as recursive and online estimation similar 1-D case. This approach is illustrated by...
In this paper, we present the alpha-EM algorithm for factor model estimation for given sample covariance. The alpha-EM includes the traditional log-EM as its proper subset. Since we use log-EM for factor analysis, however, it is shown that alpha-EM can also be used on factor analysis and more important the convergence speed of the alpha-EM is much faster than log-EM. It also allows us to choose different...
In the context of a magnetic field-based indoor location system, this paper proposes a feature extraction process that uses magnetic-field temporal and spectral features in order to develop a classification model of indoor places, using only a magnetometer included in popular smartphones. We initially propose 46 features, 26 derived from the spectral evolution and 20 from the temporal one, chosen...
In a recent paper, Cucker and Smale proposed a multi-agent model to study the flocking behavior, where they assume that all agents can interact with all other agents. Though this model attracted much attention of researchers, the global interactions used in that paper changed the nature of multi-agent systems. In this paper we will investigate a new flocking model, in which the global interactions...
We focus on the estimation of the fuzzy linear regression model where the explanatory and response variables are both L fuzzy numbers. A method is proposed to fit this regression model and the resulting estimates of the parameters are shown to be asymptotically normal and consistent. Furthermore, some simulation experiments are conducted to evaluate the performance of the proposed method. The results...
In this paper, we present a cloud-based epidemic simulation framework which is designed for simulating the spread of epidemic diseases globally. We enhance the SEIR, a popular global equation model for infection diseases study. The original SEIR model takes long to generate results. Hence, we modify SEIR by adding the level of severity into each of the epidemic state. Therefore, the time period is...
Performance estimation of an application on any processor is becoming a essential task, specially when the processor is used for high performance computing. Our work here presents a model to estimate performance of various applications on a modern GPU. Recently, GPUs are getting popular in the area of high performance computing along with original application domain of graphics. We have chosen FERMI...
The large amount of calculation always severely restricts the application domain expansion of particle filter, a novel multi-sensor multiple model particle filtering algorithm based on particle weight optimization is proposed. In the multiple model particle filter framework, the optimization method of particle weight is realized by the extraction and utilization of redundancy and complementary information...
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