Results 1  10
of
7,113
Sequential data assimilation with a nonlinear quasigeostrophic model using Monte Carlo methods to forecast error statistics
 J. Geophys. Res
, 1994
"... . A new sequential data assimilation method is discussed. It is based on forecasting the error statistics using Monte Carlo methods, a better alternative than solving the traditional and computationally extremely demanding approximate error covariance equation used in the extended Kalman filter. The ..."
Abstract

Cited by 800 (23 self)
 Add to MetaCart
. The unbounded error growth found in the extended Kalman filter, which is caused by an overly simplified closure in the error covariance equation, is completely eliminated. Open boundaries can be handled as long as the ocean model is well posed. Wellknown numerical instabilities associated with the error
ModelBased Clustering, Discriminant Analysis, and Density Estimation
 JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
, 2000
"... Cluster analysis is the automated search for groups of related observations in a data set. Most clustering done in practice is based largely on heuristic but intuitively reasonable procedures and most clustering methods available in commercial software are also of this type. However, there is little ..."
Abstract

Cited by 573 (29 self)
 Add to MetaCart
, there is little systematic guidance associated with these methods for solving important practical questions that arise in cluster analysis, such as \How many clusters are there?", "Which clustering method should be used?" and \How should outliers be handled?". We outline a general methodology
Contour Tracking By Stochastic Propagation of Conditional Density
, 1996
"... . In Proc. European Conf. Computer Vision, 1996, pp. 343356, Cambridge, UK The problem of tracking curves in dense visual clutter is a challenging one. Trackers based on Kalman filters are of limited use; because they are based on Gaussian densities which are unimodal, they cannot represent s ..."
Abstract

Cited by 661 (23 self)
 Add to MetaCart
simultaneous alternative hypotheses. Extensions to the Kalman filter to handle multiple data associations work satisfactorily in the simple case of point targets, but do not extend naturally to continuous curves. A new, stochastic algorithm is proposed here, the Condensation algorithm  Conditional
Synchronous data flow
, 1987
"... Data flow is a natural paradigm for describing DSP applications for concurrent implementation on parallel hardware. Data flow programs for signal processing are directed graphs where each node represents a function and each arc represents a signal path. Synchronous data flow (SDF) is a special case ..."
Abstract

Cited by 622 (45 self)
 Add to MetaCart
of data flow (either atomic or large grain) in which the number of data samples produced or consumed by each node on each invocation is specified a priori. Nodes can be scheduled statically (at compile time) onto single or parallel programmable processors so the runtime overhead usually associated
Least squares quantization in pcm.
 Bell Telephone Laboratories Paper
, 1982
"... AbstractIt has long been realized that in pulsecode modulation (PCM), with a given ensemble of signals to handle, the quantum values should be spaced more closely in the voltage regions where the signal amplitude is more likely to fall. It has been shown by Panter and Dite that, in the limit as t ..."
Abstract

Cited by 1362 (0 self)
 Add to MetaCart
AbstractIt has long been realized that in pulsecode modulation (PCM), with a given ensemble of signals to handle, the quantum values should be spaced more closely in the voltage regions where the signal amplitude is more likely to fall. It has been shown by Panter and Dite that, in the limit
MapReduce: Simplified data processing on large clusters.
 In Proceedings of the Sixth Symposium on Operating System Design and Implementation (OSDI04),
, 2004
"... Abstract MapReduce is a programming model and an associated implementation for processing and generating large data sets. Programs written in this functional style are automatically parallelized and executed on a large cluster of commodity machines. The runtime system takes care of the details of ..."
Abstract

Cited by 3439 (3 self)
 Add to MetaCart
Abstract MapReduce is a programming model and an associated implementation for processing and generating large data sets. Programs written in this functional style are automatically parallelized and executed on a large cluster of commodity machines. The runtime system takes care of the details
A solution to the simultaneous localization and map building (SLAM) problem
 IEEE Transactions on Robotics and Automation
, 2001
"... Abstractâ€”The simultaneous localization and map building (SLAM) problem asks if it is possible for an autonomous vehicle to start in an unknown location in an unknown environment and then to incrementally build a map of this environment while simultaneously using this map to compute absolute vehicle ..."
Abstract

Cited by 505 (30 self)
 Add to MetaCart
using millimeterwave (MMW) radar to provide relative map observations. This implementation is used to demonstrate how some key issues such as map management and data association can be handled in a practical environment. The results obtained are crosscompared with absolute locations of the map
Fast linear iterations for distributed averaging.
 Systems & Control Letters,
, 2004
"... Abstract We consider the problem of finding a linear iteration that yields distributed averaging consensus over a network, i.e., that asymptotically computes the average of some initial values given at the nodes. When the iteration is assumed symmetric, the problem of finding the fastest converging ..."
Abstract

Cited by 433 (12 self)
 Add to MetaCart
converging linear iteration can be cast as a semidefinite program, and therefore efficiently and globally solved. These optimal linear iterations are often substantially faster than several common heuristics that are based on the Laplacian of the associated graph. We show how problem structure can
Specification, Formal Verification and Implementation of Tasks and Missions for an Autonomous Vehicle
, 1995
"... This paper describes the use of modern approaches of formal verification of behavioral and temporal temporties in an experimentation of automatic vehicle following. We firstly recall the key concepts of the proposed specification method: the robottask, which allows to describe in a structured way a ..."
Abstract

Cited by 1 (1 self)
 Add to MetaCart
an automatic control law and the associated discreteevent handling; the robotprocedure, which is the specification of complex missions from the logical point of view. We then present the used environment (Orccad) and verification tools, based on the use of synchronous languages for the reactive part
Recognition of visual activities and interactions by stochastic parsing
 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 2000
"... This paper describes a probabilistic syntactic approach to the detection and recognition of temporally extended activities and interactions between multiple agents. The fundamental idea is to divide the recognition problem into two levels. The lower level detections are performed using standard inde ..."
Abstract

Cited by 322 (8 self)
 Add to MetaCart
level detections, and allow the inclusion of a priori knowledge about the structure of temporal events in a given domain. To achieve such a system we: 1) provide techniques for generating a discrete symbol stream from continuous lowlevel detectors; 2) extend stochastic contextfree parsing to handle uncertainty
Results 1  10
of
7,113