In combinatorial optimization, a popular approach to NP-hard problems is the design of approximation algorithms. These algorithms typically run in polynomial time and are guarante...
As an example of the recently introduced concept of rate of innovation, signals that are linear combinations of a finite number of Diracs per unit time can be acquired by linear fi...
In traditional framework of Compressive Sensing (CS), only sparse prior on the property of signals in time or frequency domain is adopted to guarantee the exact inverse recovery. ...
In this paper, we present a new approach based on Markov Chain Monte Carlo(MCMC) for the stable monocular tracking of variable interacting targets in 3D space. The crucial problem...
— In the simultaneous localization and mapping (SLAM) problem, a mobile robot must build a map of its environment while simultaneously determining its location within that map. W...