Bloch-McConnell方程参数辨识逆问题的精确解。纵向磁化

IF 2 3区化学 Q3 BIOCHEMICAL RESEARCH METHODS

Journal of magnetic resonance Pub Date : 2025-03-30 DOI:10.1016/j.jmr.2025.107873

Ivan Argatov, Vitaly Kocherbitov

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引用次数: 0

摘要

考虑了一个由两个线性一阶微分Bloch-McConnell方程组成的二元磁交换模型。在零初始条件下，用纵向磁化情况下导出的通解的对称形式描述了弛豫和交换行为。在对交换参数和弛豫参数有少许先验知识的情况下，用解析显式精确地求解了具有有限磁化信息的逆问题。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Exact solution of the parameter identification inverse problem for the Bloch–McConnell equations. Longitudinal magnetization

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Exact solution of the parameter identification inverse problem for the Bloch–McConnell equations. Longitudinal magnetization

A two-site magnetic exchange model comprising a set of two linear first-order differential Bloch–McConnell equations is considered. The relaxation and exchange behavior is described using a symmetrical form of the general solution derived in the case of longitudinal magnetization for the zero initial conditions. The inverse problem with limited magnetization information has been solved exactly in an analytical explicit form under mild a priori knowledge about the exchange and relaxation parameters.

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来源期刊

Journal of magnetic resonance 物理-光谱学

CiteScore

3.80

自引率

13.60%

发文量

150

审稿时长

69 days

期刊介绍： The Journal of Magnetic Resonance presents original technical and scientific papers in all aspects of magnetic resonance, including nuclear magnetic resonance spectroscopy (NMR) of solids and liquids, electron spin/paramagnetic resonance (EPR), in vivo magnetic resonance imaging (MRI) and spectroscopy (MRS), nuclear quadrupole resonance (NQR) and magnetic resonance phenomena at nearly zero fields or in combination with optics. The Journal''s main aims include deepening the physical principles underlying all these spectroscopies, publishing significant theoretical and experimental results leading to spectral and spatial progress in these areas, and opening new MR-based applications in chemistry, biology and medicine. The Journal also seeks descriptions of novel apparatuses, new experimental protocols, and new procedures of data analysis and interpretation - including computational and quantum-mechanical methods - capable of advancing MR spectroscopy and imaging.