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Incomplete matrix partial fraction expansion ∗ by
"... Abstract: The paper presents a method for computing a matrix partial fraction when a complete set of solvents for the "denominator" matrix polynomial does not exist. Partial fraction expansion is a useful tool of analysis and of decomposition of multiple input, multiple output linear time ..."
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Abstract: The paper presents a method for computing a matrix partial fraction when a complete set of solvents for the "denominator" matrix polynomial does not exist. Partial fraction expansion is a useful tool of analysis and of decomposition of multiple input, multiple output linear time
An Improved Heaviside Approach to Partial Fraction Expansion and its Applications
"... Abstract—An improved Heaviside approach to compute the partial fraction expansions of proper rational functions is presented. This method involves simple substitutions and polynomial divisions only, without the use of differentiation or solution of a system of linear equations. Examples on its appli ..."
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Abstract—An improved Heaviside approach to compute the partial fraction expansions of proper rational functions is presented. This method involves simple substitutions and polynomial divisions only, without the use of differentiation or solution of a system of linear equations. Examples on its
Modern Information Retrieval
, 1999
"... Information retrieval (IR) has changed considerably in the last years with the expansion of the Web (World Wide Web) and the advent of modern and inexpensive graphical user interfaces and mass storage devices. As a result, traditional IR textbooks have become quite outofdate which has led to the i ..."
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Cited by 3233 (29 self)
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Information retrieval (IR) has changed considerably in the last years with the expansion of the Web (World Wide Web) and the advent of modern and inexpensive graphical user interfaces and mass storage devices. As a result, traditional IR textbooks have become quite outofdate which has led
CURE: An Efficient Clustering Algorithm for Large Data sets
 Published in the Proceedings of the ACM SIGMOD Conference
, 1998
"... Clustering, in data mining, is useful for discovering groups and identifying interesting distributions in the underlying data. Traditional clustering algorithms either favor clusters with spherical shapes and similar sizes, or are very fragile in the presence of outliers. We propose a new clustering ..."
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Cited by 722 (5 self)
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and then shrinking them toward the center of the cluster by a specified fraction. Having more than one representative point per cluster allows CURE to adjust well to the geometry of nonspherical shapes and the shrinking helps to dampen the effects of outliers. To handle large databases, CURE employs a combination
Confirmation Bias: A Ubiquitous Phenomenon in Many Guises
 Review of General Psychology
, 1998
"... Confirmation bias, as the term is typically used in the psychological literature, connotes the seeking or interpreting of evidence in ways that are partial to existing beliefs, expectations, or a hypothesis in hand. The author reviews evidence of such a bias in a variety of guises and gives examples ..."
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Cited by 314 (0 self)
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Confirmation bias, as the term is typically used in the psychological literature, connotes the seeking or interpreting of evidence in ways that are partial to existing beliefs, expectations, or a hypothesis in hand. The author reviews evidence of such a bias in a variety of guises and gives
The stages of economic growth.
 Economic History Review , 2nd series 12,
, 1959
"... JSTOR is a notforprofit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about J ..."
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Cited by 297 (0 self)
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sectoral paths. At any period of time, the rate of growth in the sectors will vary greatly; and it is possible to isolate empirically certain readings sectors, at early stages of their evolution, whose rapid rate of expansion plays an essential direct and indirect role in maintaining the overall momentum
Coalition Structure Generation with Worst Case Guarantees
, 1999
"... Coalition formation is a key topic in multiagent systems. One may prefer a coalition structure that maximizes the sum of the values of the coalitions, but often the number of coalition structures is too large to allow exhaustive search for the optimal one. Furthermore, finding the optimal coalition ..."
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Cited by 270 (9 self)
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structure is NPcomplete. But then, can the coalition structure found via a partial search be guaranteed to be within a bound from optimum? We show that none of the previous coalition structure generation algorithms can establish any bound because they search fewer nodes than a threshold that we show
Full Partial Fraction Decomposition of Rational Functions
 157160. Proceedings ISSAC'93
, 1993
"... We describe a rational algorithm that computes the full partial fraction expansion of a rational function over the algebraic closure of its field of definition. The algorithm uses only gcd operations over the initial field but the resulting decomposition is expressed with linear denominators. We giv ..."
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Cited by 6 (3 self)
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We describe a rational algorithm that computes the full partial fraction expansion of a rational function over the algebraic closure of its field of definition. The algorithm uses only gcd operations over the initial field but the resulting decomposition is expressed with linear denominators. We
Stochastic Partial Differential Equations driven by . . .
, 2004
"... In this paper we develop a white noise framework for the study of stochastic partial differential equations driven by a dparameter (pure jump) Lévy white noise. As an example we use this theory to solve the stochastic Poisson equation with respect to Lévy white noise for any dimension d. The soluti ..."
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Cited by 183 (8 self)
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In this paper we develop a white noise framework for the study of stochastic partial differential equations driven by a dparameter (pure jump) Lévy white noise. As an example we use this theory to solve the stochastic Poisson equation with respect to Lévy white noise for any dimension d
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