Novel Constrained Least Squares Algorithms With Application to MEG

新颖的约束最小二乘算法在 MEG 中的应用

• 批准号: 9220550
• 负责人: Bhaskar Rao
• 金额: $ 16.83万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-04-15 至 1997-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9220550&HistoricalAwards=false
• 关键词: Novel; Constrained; Least; Squares; Algorithms

Rao This research is studying novel algorithms for computing solutions to least squares problems with constraints, especially those problems that are underdetermined. The primary application is expected to be in Magnetoencephalography (MEG), a potentially new modality for the imaging of the brain. Both algorithm development and analysis are being considered, with MEG providing the forum for the testing and evaluation of these algorithms. It is expected that this research will greatly enhance our understanding of nonlinear iterative techniques.

Rao 这项研究正在研究新颖的算法，用于计算具有约束的最小二乘问题的解决方案，特别是那些不确定的问题。预计主要应用是脑磁图（MEG），这是一种潜在的大脑成像新模式。算法开发和分析都在考虑之中，MEG 为这些算法的测试和评估提供了论坛。预计这项研究将极大地增强我们对非线性迭代技术的理解。