describe a particular case of such methods for interfaces whose speed depends only on local position. The technique works by coupling work on entropy conditions for interface motion, the theory of viscosity solutions for Hamilton-Jacobi equations and fast adaptive narrow band level set methods

of object boundaries. The resulting equation of motion is solved by employing entropy-satisfying upwind finite difference schemes. We present a variety of ways of computing evolving front, including narrow bands, reinitializations, and different stopping criteria. The efficacy of the scheme is demonstrated

with constant space regardless of cell density. We study and evaluate link estimator, neighborhood table management, and reliable routing protocol techniques. We focus on a many-to-one, periodic data collection workload. We narrow the design space through evaluations on large-scale, high-level simulations to 50

was widely studied in computer vision and graphics communities. We provide links to a large number of known extensions based on iterative parameter re-estimation and learning, multi-scale or hierarchical approaches, narrow bands, and other techniques for demanding photo, video, and medical applications.

of the narrow-band algorithm. The new algorithm packs the level-set isosurface data into 2D texture memory via a multidimensional virtual memory system. As the level set moves, this texture-based representation is dynamically updated via a novel GPU-to-CPU message passing scheme. By integrating the level

Narrow Band Method) is proposed. FNB is based on the Narrow Band Method (NB) which is the well-known fast method of the Level Set Method. The main idea is to exploit the combinative use of the narrow band and the approximate distance from the front. The method has been applied in several experiments

The amount of training data has a crucial effect on the accuracy of HMM based meeting recognition systems. Conversational telephone speech matches speech in meetings well. However it is naturally recorded with low bandwidth. In this paper we present a scheme that allows to transform wide-band

recognition

considered as narrow-band inter-ferers. Because UWB systems are highly susceptible to narrow-band interferers, there is a demand for interferer suppression. An adaptive filter consisting of a two-element diversity receiver that performs minimum mean square error combining (MMSE) by the LMS algorithm

We propose an operator-based method of adaptive signal decomposition, whereby a local narrow band signal is defined in the null space of a singular local linear operator. Based on the definition and the algorithm, we propose two types of local narrow band signals and two singular operator