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Canadian Journal of Mathematics, 1974
All functions mentioned in this paper will be real-valued. If f1, f2, g are nonnegative functions on a set S that satisfy g ≦ f1 + f2, the Riesz decomposition problem associated with these data is to find functions gi on S such thatThe formulaalways furnishes a solution.
Nagel, Alexander, Rudin, Walter
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All functions mentioned in this paper will be real-valued. If f1, f2, g are nonnegative functions on a set S that satisfy g ≦ f1 + f2, the Riesz decomposition problem associated with these data is to find functions gi on S such thatThe formulaalways furnishes a solution.
Nagel, Alexander, Rudin, Walter
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AAAI Spring Symposium: MLPS, 2020
We propose a generalized space-time domain decomposition framework for the physics-informed neural networks (PINNs) to solve nonlinear partial differential equations (PDEs) on arbitrary complex-geometry domains.
Ameya Dilip Jagtap, G. Karniadakis
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We propose a generalized space-time domain decomposition framework for the physics-informed neural networks (PINNs) to solve nonlinear partial differential equations (PDEs) on arbitrary complex-geometry domains.
Ameya Dilip Jagtap, G. Karniadakis
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SSRN Electronic Journal, 2017
The relation between Sen's decomposition of the weak axiom of revealed preferences (WARP), and WARP directional decomposition introduced in Nosratabadi (2017) is investigated. It is argued that the latter generalizes the former. A pairwise transitive WARP decomposition consistent with Sen's property a is given.
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The relation between Sen's decomposition of the weak axiom of revealed preferences (WARP), and WARP directional decomposition introduced in Nosratabadi (2017) is investigated. It is argued that the latter generalizes the former. A pairwise transitive WARP decomposition consistent with Sen's property a is given.
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A Data–Driven Approximation of the Koopman Operator: Extending Dynamic Mode Decomposition
Journal of nonlinear science, 2014The Koopman operator is a linear but infinite-dimensional operator that governs the evolution of scalar observables defined on the state space of an autonomous dynamical system and is a powerful tool for the analysis and decomposition of nonlinear ...
Matthew O. Williams +2 more
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2021
This chapter carefully attends to how decomposition principles are supposed to work, and how different variants and formulations affect the resulting theory in different ways. It begins with the philosophically familiar notion of Boolean complementation, and then gradually discusses ever weaker variants of this notion in the form of various ...
A. J. Cotnoir, Achille C. Varzi
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This chapter carefully attends to how decomposition principles are supposed to work, and how different variants and formulations affect the resulting theory in different ways. It begins with the philosophically familiar notion of Boolean complementation, and then gradually discusses ever weaker variants of this notion in the form of various ...
A. J. Cotnoir, Achille C. Varzi
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Successive variational mode decomposition
Signal Processing, 2020Variational mode decomposition (VMD) is a powerful technique for concurrently decomposing a signal into its constituent intrinsic modes. However, the performance of VMD will be degraded if the number of modes available in the signal is not precisely ...
M. Nazari, S. M. Sakhaei
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From the Sup-Decomposition to Sequential Decompositions
Journal of Mathematical Imaging and Vision, 2001zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hashimoto, Ronaldo Fumio +1 more
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Catalysis from A to Z, 2020
The energy decomposition analysis (EDA) is a powerful method for a quantitative interpretation of chemical bonds in terms of three major expressions.
Moritz von Hopffgarten, G. Frenking
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The energy decomposition analysis (EDA) is a powerful method for a quantitative interpretation of chemical bonds in terms of three major expressions.
Moritz von Hopffgarten, G. Frenking
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Vascular decomposition using weighted approximate convex decomposition
International Journal of Computer Assisted Radiology and Surgery, 2012Stroke treatment often requires analysis of vascular pathology evaluated using computed tomography (CT) angiography. Due to vascular variability and complexity, finding precise relationships between vessel geometries and arterial pathology is difficult.
Ashirwad, Chowriappa +6 more
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Value-Decomposition Networks For Cooperative Multi-Agent Learning Based On Team Reward
Adaptive Agents and Multi-Agent Systems, 2018We study the problem of cooperative multi-agent reinforcement learning with a single joint reward signal. This class of learning problems is difficult because of the often large combined action and observation spaces.
P. Sunehag +10 more
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