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Ski jumping, a prestigious Olympic discipline, has been constantly evolving. Over the years, the biomechanics fundamentals of this highly technical sport have been intensively documented by investigating the jump timing, kinematics, dynamics and motor cont ...
Closed-form solutions are traditionally used in computer vision for estimating rigid body transformations. Here we suggest an iterative solution for estimating rigid body transformations and prove its global convergence. We show that for a number of applic ...
We consider the denoising of signals and images using regularized least-squares method. In particular, we propose a simple minimization algorithm for regularizers that are functions of the discrete gradient. By exploiting the connection of the discrete gra ...
We consider the denoising of signals and images using regularized least-squares method. In particular, we propose a simple minimization algorithm for regularizers that are functions of the discrete gradient. By exploiting the connection of the discrete gr ...
In the recent years, global climate change has induced evergrowing loss of sea ice in the Arctic. As the sea ice disappears, albedo diminishes and the sea surface is more likely to be warmed by incoming solar radiation. With the right wind conditions, this ...
The rate distortion behavior of sparse memoryless sources is studied. These serve as models of sparse signal representations and facilitate the performance analysis of "sparsifying" transforms like the wavelet transform and nonlinear approximation schemes. ...
Institute of Electrical and Electronics Engineers2012
Heat transfer coefficients for enhanced tubes are typically measured indirectly using the "Wilson plot" method to first characterize the thermal performance of the one side (heating or cooling supply) and then to obtain the heat transfer data for the enhan ...
Estimation of a vector from quantized linear measurements is a common problem for which simple linear techniques are suboptimal—sometimes greatly so. This paper develops message-passing de-quantization (MPDQ) algorithms for minimum mean-squared error estim ...
We investigate the problem of the optimal reconstruction of a generalized Poisson process from its noisy samples. The process is known to have a finite rate of innovation since it is generated by a random stream of Diracs with a finite average number of i ...
We investigate the problem of the optimal reconstruction of a generalized Poisson process from its noisy samples. The process is known to have a finite rate of innovation since it is generated by a random stream of Diracs with a finite average number of im ...
