Optical nonlinear Fourier transform-based communication systems require an accurate estimation of a signal's nonlinear spectrum, computed usually by piecewise approximation methods on the signal samples. We propose an algorithm, named successive eigenvalue removal, to improve the spectrum estimation of a multi-soliton pulse. It exploits a property of the Darboux transform that allows removing eigenvalues from the nonlinear spectrum. This results in a smaller pulse duration and smaller bandwidth. The spectral coefficients are estimated successively after removing the eigenvalues of a signal. As a beneficial application, we show that the algorithm decreases the computational complexity by iteratively reducing the pulse duration.

中文翻译：

---

多孤子谱幅度估计的连续特征值去除

基于光学非线性傅立叶变换的通信系统需要对信号的非线性频谱进行准确估计，通常通过对信号样本的分段逼近方法进行计算。我们提出了一种称为连续特征值去除的算法，以改进多孤子脉冲的频谱估计。它利用了 Darboux 变换的一个特性，该特性允许从非线性谱中去除特征值。这导致更小的脉冲持续时间和更小的带宽。去除信号的特征值后，连续估计频谱系数。作为一个有益的应用，我们表明该算法通过迭代减少脉冲持续时间来降低计算复杂度。