欠定的

Solving Underdetermined Systems with Interval Methods, Reliable Computing, 5(1)(1999): 23-33. 目前的研究課題為：反問題的數(shù)值計算方法。

Solving underdetermined blind source separation (BSS) via sparse representation has become a hot spot recently. 摘要 借助稀疏表示解決欠定盲源分離（BSS）是目前研究的一個熱點。

Based on independent component analysis, a new way of underdetermined BSS composed of SVD-ICA and determined-ICA is put forward in this paper. 該文根據(jù)獨立分量分析ICA理論，提出了多源少信道（欠定）ICA算法與完備ICA算法結(jié)合的二次盲信號分離方法，用此方法對局部放電脈沖進(jìn)行提取。

This paper discusses the recoverability of underdetermined blind source separation(BSS),based on a two-stage sparse representation approach. 基于一種兩步稀疏表示的方法,利用隨機(jī)框架討論欠定盲源分離的恢復(fù)能力。

As for underdetermined system of equation, reconstructing tomography of LSQR and ART algorithms cannot accurately show smaller abnormal body. 對欠定方程組，兩種算法的重建圖像均難于正確反映尺度較小的異常體。

Using distributed source model, this imaging problem can be formulated as an ill-conditioned and highly underdetermined linear inverse problem. 采用非參數(shù)的分布源模型,磁源成象問題即為求解一病態(tài)的欠定的線性方程組。