论文标题
最小二乘近似中的权重测定最大驱动的测定
Maximal-entropy driven determination of weights in least-square approximation
论文作者
论文摘要
我们利用了在信息理论和统计热力学中成功测试的最大 - 内向方法的想法，以确定函数的系数和平方错误的权重作为在最小二乘近似中的一个单个问题的输出。我们通过将多项式作为第一步，通过将其应用于代表性测试案例的能力和性能提供证据。我们通过为将来的工作提出建议，以改善本文中提出的方法的版本来结束。
We exploit the idea to use the maximal-entropy method, successfully tested in information theory and statistical thermodynamics, to determine approximating function's coefficients and squared errors' weights simultaneously as output of one single problem in least-square approximation. We provide evidence of the method's capabilities and performance through its application to representative test cases by working with polynomials as a first step. We conclude by formulating suggestions for future work to improve the version of the method we present in this paper.
