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Sequential Monte Carlo Techniques for Solving Non-Linear Systems

机译:解决非线性系统的顺序蒙特卡洛技术

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Given a system of m equations F(x) = 0 (where m is large and x is an unknown m-vector), we seek to apply sequential Monte Carlo [SMC] methods to find solutions efficiently. This paper follows up on a previous paper by the same author, in which consideration was limited to linear systems of the form Ax = a (where, again, m is large, A is a known (m x m) matrix, a is a known m-vector, and x is an unknown m-vector). It was shown there that effective techniques could reduce computation times dramatically (speed-up factors of 550 to 26,000 were obtained in sample calculations). The methods presented here rely on the use of Newtonian linearization, combined with the SMC methods previously described. Incidentally, the optimization of these SMC methods is discussed here and should clarify the parametrization of the SMC techniques so as to yield the highest efficiency.
机译:给定一个由m个方程组成的系统F(x)= 0(其中m大,x是未知的m-向量),我们寻求应用顺序蒙特卡洛[SMC]方法来有效地找到解。本文是同一位作者的前一篇论文的后续文章,其中只考虑了形式为Ax = a的线性系统(其中,m很大,A是已知的(mxm)矩阵,a是已知的m -向量,而x是未知的m-向量)。结果表明,有效的技术可以显着减少计算时间(在样本计算中获得了550至26,000的加速因子)。这里介绍的方法依赖于牛顿线性化的使用,并结合了先前描述的SMC方法。顺便说一下,这里讨论了这些SMC方法的优化,并应阐明SMC技术的参数化,以产生最高效率。

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