Results 201 to 210 of about 58,671 (260)
Electrocapillary Modulated Interfacial Tension Amplifies Liquid Metal Transduction
Advanced Functional Materials, EarlyView.This study presented an electrocapillary‐enhanced magnetohydrodynamic pumping strategy that harnesses the Lorentz force and interfacial tension modulation of liquid metal droplets to achieve amplified fluidic power. The system enabled low‐voltage, self‐oscillating fluidic transduction with enhanced pressure and flow generation, supporting compact ...
Saba Firouznia +3 more
wiley +1 more source
Thermal Effects in Microfluidic Electrokinetic Flows: From Limitation to Design Opportunity. [PDF]
Micromachines (Basel)Roy T.
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Rapid wavefront shaping using an optical gradient acquisition. [PDF]
Nat CommunMonin S, Alterman M, Levin A.
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Design and cutting performance analysis of cylindrical gear skiving tool with uniform working rake angle. [PDF]
Sci RepJi J +5 more
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Green Synthesis of a Hyaluronan-Based Multimeric A9 Peptide System: Polysaccharide-A9 Conjugate with Enhanced HER2 Receptor Binding Affinity and Potential Biomedical Applications as an Active Material. [PDF]
BiomacromoleculesVerdoliva V +3 more
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Closed-Loop Iterative Self-Calibration of Initial Phase in Phased Arrays. [PDF]
Sensors (Basel)Huang X, Huang D, Chen B, Wu B.
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WIREs Computational Statistics, 2001
AbstractThe conjugate gradient (CG) method for optimization and equation solving is described, along with three principal families of algorithms derived from it. In each case, a foundational CG algorithm is formulated mathematically and followed by a brief discussion of refinements and variants within its family.
Saul I. Gass, Carl M. Harris
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AbstractThe conjugate gradient (CG) method for optimization and equation solving is described, along with three principal families of algorithms derived from it. In each case, a foundational CG algorithm is formulated mathematically and followed by a brief discussion of refinements and variants within its family.
Saul I. Gass, Carl M. Harris
openaire +2 more sources
2020
The conjugate gradient method was published by Hestenes and Stiefel in 1952, as a direct method for solving linear systems. Today its main use is as an iterative method for solving large sparse linear systems. On a test problem we show that it performs as well as the SOR method with optimal acceleration parameter, and we do not have to estimate any ...
Tom Lyche, Georg Muntingh, Øyvind Ryan
+4 more sources
The conjugate gradient method was published by Hestenes and Stiefel in 1952, as a direct method for solving linear systems. Today its main use is as an iterative method for solving large sparse linear systems. On a test problem we show that it performs as well as the SOR method with optimal acceleration parameter, and we do not have to estimate any ...
Tom Lyche, Georg Muntingh, Øyvind Ryan
+4 more sources
Deconvolution by the conjugate gradient method
ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005Since it is practically difficult to generate and propagate an impulse, often a system is excited by a narrow time domain pulse. The output is recorded and then a numerical deconvolution is often done to extract the impulse response of the object.
Tapan K. Sarkar +3 more
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Complex conjugate gradient methods
Numerical Algorithms, 1993The paper is concerned with the solution of linear systems with non- singular complex matrices. A unified framework is presented from which various conjugate gradient-like methods for solving the above described systems are derived. The considered methods include both well-known methods and some new variants of these methods.
Pascal Joly, Gérard Meurant
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