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首页> 外文期刊>Inverse Problems: An International Journal of Inverse Problems, Inverse Methods and Computerised Inversion of Data >An alternating iterative minimisation algorithm for the double-regularised total least square functional
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An alternating iterative minimisation algorithm for the double-regularised total least square functional

机译:双正则化总最小二乘泛函的交替迭代最小化算法

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The total least squares (TLS) method is a successful approach for linear problems if both the right-hand side and the operator are contaminated by some noise. For ill-posed problems, a regularisation strategy has to be considered to stabilise the computed solution. Recently a double regularised TLS method was proposed within an infinite dimensional setup and it reconstructs both function and operator, reflected on the bilinear forms Our main focuses are on the design and the implementation of an algorithm with particular emphasis on alternating minimisation strategy, for solving not only the double regularised TLS problem, but a vast class of optimisation problems: on the minimisation of a bilinear functional of two variables.
机译:如果右侧和操作员均受到某些​​噪声污染,则总最小二乘法(TLS)是解决线性问题的成功方法。对于不适定的问题,必须考虑使用正则化策略来稳定计算的解。最近,在无限维设置中提出了一种双正则TLS方法,该方法重构了函数和算子,并反映在双线性形式上。我们的主要重点是算法的设计和实现,尤其着重于交替最小化策略,只有双重正则化TLS问题,而是一大类优化问题:关于两个变量的双线性函数的最小化。

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