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In this paper, an entropy-based method is proposed to forecast the demographical changes of countries. We formulate the estimation of future demographical profiles as a constrained optimization problem, anchored on the empirically validated assumption that the entropy of age distribution is increasing in time. The procedure of the proposed method involves three stages, namely: 1) Prediction of the...
The parameter estimation to mixture models has been shown as a local optimal solution for decades. In this paper, we propose a functional estimation to mixture models using step functions. We show that the proposed functional inference yields a convex formulation and consequently the mixture models are feasible for a global optimum inference. The proposed approach further unifies the existing isolated...
In this paper, a robust homography estimation method is proposed to match multiview images in the uncalibrated case. This method formulates a new loss function to verify homography hypothesis, which combines models of key-point consensus and appearance similarity. In the consensus model, Lap lace distribution is exploited to better characterize the imprecision of key points. And in the appearance...
Diffusion Tensor Magnetic Resonance Imaging (DT-MRI) is an emerging technique that explores the structural connectivity of the human brain. The probabilistic fiber tractography based on DT-MRI data behaves more robustly than deterministic approaches in the presence of fiber crossings, but requires more prohibitive computational time. In this work we present a GPU-based probabilistic framework for...
Recently, many low-cost micro electro mechanical systems (MEMS) IMUs have emerged for only several hundred US dollars. In comparison to high-end IMUs, an entire Inertial Navigation System (INS) can be implemented with smaller size/volume, lower weight and costs. On the other hand, they have a relatively lower accuracy due to their larger systematic errors, such as bias, scale factor and drift, which...
We consider the problem of single image object motion deblurring from a static camera. It is well-known that deblurring of moving objects using a traditional camera is ill-posed, due to the loss of high spatial frequencies in the captured blurred image. A coded exposure camera modulates the integration pattern of light by opening and closing the shutter within the exposure time using a binary code...
As transistor feature size scales down, re-convergence takes more and more significant effect to SER (soft error rate) estimation in combinational logic. In this paper, we propose 4 forms of re-convergence in 2-input logic gates, ROR, RSUB, RAND and RXOR, and for each form the sensitization condition is presented. The results are extended to more complex gates. Based on our re-convergence analysis...
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