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1,928
Predictive PIControl of Linear Plants under Positional and Incremental Input Saturations
 in Proc. IFAC World Triennal Congress
, 1999
"... A predictive control strategy is developed for setpoint tracking of LTI plants in the presence of joint positional and incremental (rate) input saturation constraints. The resulting control algorithm is built so as to provide an integral action capable to asymptotically reject arbitrary constant di ..."
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Cited by 2 (1 self)
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A predictive control strategy is developed for setpoint tracking of LTI plants in the presence of joint positional and incremental (rate) input saturation constraints. The resulting control algorithm is built so as to provide an integral action capable to asymptotically reject arbitrary constant
The Quickhull algorithm for convex hulls
 ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE
, 1996
"... The convex hull of a set of points is the smallest convex set that contains the points. This article presents a practical convex hull algorithm that combines the twodimensional Quickhull Algorithm with the generaldimension BeneathBeyond Algorithm. It is similar to the randomized, incremental algo ..."
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Cited by 713 (0 self)
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The convex hull of a set of points is the smallest convex set that contains the points. This article presents a practical convex hull algorithm that combines the twodimensional Quickhull Algorithm with the generaldimension BeneathBeyond Algorithm. It is similar to the randomized, incremental
BIRCH: an efficient data clustering method for very large databases
 In Proc. of the ACM SIGMOD Intl. Conference on Management of Data (SIGMOD
, 1996
"... Finding useful patterns in large datasets has attracted considerable interest recently, and one of the most widely st,udied problems in this area is the identification of clusters, or deusel y populated regions, in a multidir nensional clataset. Prior work does not adequately address the problem of ..."
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Cited by 576 (2 self)
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of large datasets and minimization of 1/0 costs. This paper presents a data clustering method named Bfll (;”H (Balanced Iterative Reducing and Clustering using Hierarchies), and demonstrates that it is especially suitable for very large databases. BIRCH incrementally and clynamicall y clusters incoming
CUTE: A Concolic Unit Testing Engine for C
 IN ESEC/FSE13: PROCEEDINGS OF THE 10TH EUROPEAN
, 2005
"... In unit testing, a program is decomposed into units which are collections of functions. A part of unit can be tested by generating inputs for a single entry function. The entry function may contain pointer arguments, in which case the inputs to the unit are memory graphs. The paper addresses the pro ..."
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Cited by 480 (22 self)
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to represent and track constraints that capture the behavior of a symbolic execution of a unit with memory graphs as inputs. Moreover, an efficient constraint solver is proposed to facilitate incremental generation of such test inputs. Finally, CUTE, a tool implementing the method is described together
A Note on the Connection Between Incremental InputtoState Stability and Fading Memory in Nonlinear Systems
"... Recently, Angeli 1 has proposed the concept of incremental inputtostate stability, which can be viewed as an extension of the wellknown inputtostate stability to the context of incremental stability. In this note, we show how the concept is connected with fading memory that has played a central ..."
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Recently, Angeli 1 has proposed the concept of incremental inputtostate stability, which can be viewed as an extension of the wellknown inputtostate stability to the context of incremental stability. In this note, we show how the concept is connected with fading memory that has played a
Incremental mapping of large cyclic environments
 In Computational Intelligence in Robotics and Automation
, 1999
"... Mobile robots can use geometric or topological maps of their environment to navigate reliably. Automatic creation of such maps is still an unrealized goal, especially in environments that have large cyclical structures. Drawing on recent techniques of global registration and correlation, we present ..."
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Cited by 332 (19 self)
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a method, called Local Registration and Global Correlation (LRGC), for reliable reconstruction of consistent global maps from dense range data. The method is attractive because it is incremental, producing an updated map with every new sensor input; and runs in constant time independent of the size
Applications of Random Sampling in Computational Geometry, II
 Discrete Comput. Geom
, 1995
"... We use random sampling for several new geometric algorithms. The algorithms are "Las Vegas," and their expected bounds are with respect to the random behavior of the algorithms. These algorithms follow from new general results giving sharp bounds for the use of random subsets in geometric ..."
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Cited by 432 (12 self)
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algorithms. These bounds show that random subsets can be used optimally for divideandconquer, and also give bounds for a simple, general technique for building geometric structures incrementally. One new algorithm reports all the intersecting pairs of a set of line segments in the plane, and requires O
A Growing Neural Gas Network Learns Topologies
 Advances in Neural Information Processing Systems 7
, 1995
"... An incremental network model is introduced which is able to learn the important topological relations in a given set of input vectors by means of a simple Hebblike learning rule. In contrast to previous approaches like the "neural gas" method of Martinetz and Schulten (1991, 1994), this m ..."
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Cited by 401 (5 self)
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An incremental network model is introduced which is able to learn the important topological relations in a given set of input vectors by means of a simple Hebblike learning rule. In contrast to previous approaches like the "neural gas" method of Martinetz and Schulten (1991, 1994
Incremental Online Learning in High Dimensions
 Neural Computation
, 2005
"... Locally weighted projection regression (LWPR) is a new algorithm for incremental nonlinear function approximation in high dimensional spaces with redundant and irrelevant input dimensions. At its core, it employs nonparametric regression with locally linear models. In order to stay computationally e ..."
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Cited by 164 (19 self)
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Locally weighted projection regression (LWPR) is a new algorithm for incremental nonlinear function approximation in high dimensional spaces with redundant and irrelevant input dimensions. At its core, it employs nonparametric regression with locally linear models. In order to stay computationally
ROAMing Terrain: Realtime Optimally Adapting Meshes
, 1997
"... Terrain visualization is a difficult problem for applications requiring accurate images of large datasets at high frame rates, such as flight simulation and groundbased aircraft testing using synthetic sensor stimulation. On current graphics hardware, the problem is to maintain dynamic, viewdepend ..."
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Cited by 287 (10 self)
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additional performance optimizations: incremental triangle stripping and prioritycomputation deferral lists. ROAM execution time is proportionate to the number of triangle changes per frame, which is typically a few percent of the output mesh size, hence ROAM performance is insensitive to the resolution
Results 1  10
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