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Implication of the thalamus in sleep alterations observed in Alzheimer's disease. [PDF]
Alzheimers DementBurnet-Merlin C, Hay YA, Brécier A.
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A Random Differential Equation Approach for Modeling the Growth of Microalgae in Photobioreactors. [PDF]
Bull Math BiolAndreu-Vilarroig C +4 more
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AI-Enhanced Hybrid QAM-PPM Visible Light Communication for Body Area Networks. [PDF]
Sensors (Basel)Shrestha S +3 more
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Laguerre-SVD reduced order modeling
IEEE 8th Topical Meeting on Electrical Performance of Electronic Packaging (Cat. No.99TH8412), 2000A reduced-order modeling method based on a system description in terms of orthonormal Laguerre functions, together with a Krylov subspace decomposition technique is presented. The link with Pade approximation, the block Arnoldi process and singular value decomposition (SVD) leads to a simple and stable implementation of the algorithm. Novel features of
L. Knockaert, D. De Zutter
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Reduced Order Stochastic Models
1988 American Control Conference, 1988This paper presents an approach to reduce the order of large-scale stochastic systems. The reduced-order model is obtained by considering only the stable modes through optimization of a steady-state error. Examples are given to illustrate the proposed method.
Craig S. Sims, Ali Feliachi
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2005
Abstract In recent years, reduced-order modeling techniques have proven to be powerful tools for various problems in circuit simulation. For example, today, reduction techniques are routinely used to replace the large RCL subcircuits that model the interconnect or the pin package of VLSI circuits by models of much smaller dimension.
Zhaojun Bai +2 more
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Abstract In recent years, reduced-order modeling techniques have proven to be powerful tools for various problems in circuit simulation. For example, today, reduction techniques are routinely used to replace the large RCL subcircuits that model the interconnect or the pin package of VLSI circuits by models of much smaller dimension.
Zhaojun Bai +2 more
openaire +1 more source