Particle Swarm Optimization and regression analysis – II

S. Mohanty
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引用次数: 2

Abstract

Abstract In the first part of this article, Particle Swarm Optimization (PSO) was applied to the problem of optimizing knot placement in the regression spline method. Although promising for broadband signals having smooth, but otherwise unknown, waveforms, this simple approach fails in the case of narrowband signals when the carrier frequency as well as the amplitude and phase modulations are unknown. A method is presented that addresses this challenge by using PSO based regression splines for the in-phase and quadrature amplitudes separately. It is thereby seen that PSO is an effective tool for regression analysis of a broad class of signals.
粒子群优化与回归分析2
摘要本文第一部分将粒子群算法(PSO)应用于回归样条法中结点布置的优化问题。虽然这种简单的方法对于具有平滑波形的宽带信号很有希望,但对于载波频率以及振幅和相位调制未知的窄带信号来说,这种方法就失败了。提出了一种解决这一问题的方法,即分别对同相幅值和正交幅值使用基于粒子群的回归样条曲线。由此可见,粒子群算法是一种有效的工具,用于回归分析的广泛类别的信号。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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