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A multi-carpooling model is proposed for the multi-vehicle carpooling problem in a distributed parallel computing environment. A two-stage stochastic optimization of the estimation of distribution algorithm solves the optimum of the multi-carpooling problem with a carpooling probabilistic matrix. A ridable matrix initiates the carpooling probabilistic matrix, and the carpooling probabilistic matrix...
Differential Synthetic Aperture Radar (SAR) Interferometry (DInSAR) coherence, a measurement of the similarity between two radar acquisitions, is a widely used index to quantitatively evaluate the quality of derived interferograms considering its direct relationship with Signal to Noise Ratio (SNR). When interferometrie measurements originate from both point-like and distributed targets, the coherence...
The purpose of this study is to develop a patient-specific dosimetry estimation system in nuclear medicine examination using a SimSET-based Monte Carlo code. We added a dose deposition routine to store the deposited energy of the photons during their flights in SimSET and developed a user-friendly interface for reading PET and CT images. Dose calculated on ORNL phantom was used to validate the accuracy...
Pulmonary characteristics differ in patients, and the suitable setting of ventilation condition is needed for every patient in the artificial respiration. The pulmonary elastance is one of the important features of lung, and it is a basis for deciding the air-way pressure limit value. In this study, an estimation method for pulmonary elastance is proposed based on functional type SIRMs fuzzy reasoning,...
A complete ultra-wideband (UWB) radar system is presented in this paper. The radar system consists of UWB CMOS radar transceiver and two compact directional UWB antennas for the purpose of transmission and reception. Different possible applications were investigated in the domain of ranging and tracking using this system along with fast and efficient signal processing algorithms. The results obtained...
This paper presents a near-optimum, low-complexity, fixed-interval smoothing algorithm that approaches the performance of an optimal smoother for the price of two low-complexity sequential estimators (two PLLs). The proposed Smoothing PLL (S-PLL) algorithm is easy to implement and fits the Cramer-Rao bounds over a wide range of signal-to-noise ratios. Moreover we show that, compared to the conventional...
In this paper, we study Bayesian and hybrid Cramer-Rao bounds (BCRB and HCRB) for the code-aided (CA) dynamical phase estimation of QAM modulated signals. In order to avoid the calculus of the inverse of the Bayesian information matrix and of the hybrid information matrix, we present some analytical expressions for the various CRBs, which greatly reduce the computation complexity.
In this paper, we study Bayesian and hybrid Cramer-Rao bounds for the dynamical phase estimation of QAM modulated signals. We present the analytical expressions for the various CRBs. This avoids the calculation of any matrix inversion and thus greatly reduces the computation complexity. Through simulations, we also illustrate the behaviors of the BCRB and of the HCRB with the signal-to-noise ratio.
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