Simulated Signal Data and Python Code for Peak Parameter Estimation

This dataset includes:Simulated Signal Data: Lorentzian and Gaussian profile signals generated under various conditions for use in spectral analysis. Python Code: Scripts used for curve fitting to extract peak parameters (intensity, bandwidth, area, and position) from the simulated signal data. These resources were developed to support the study on the precision of peak parameter estimation under the Poisson noise limit.本数据集包含以下内容： 模拟信号数据：在多种条件下生成的洛伦兹型（Lorentzian）与高斯型（Gaussian）剖面信号，用于光谱分析。 Python代码：用于曲线拟合的脚本程序，可从上述模拟信号数据中提取峰参数（强度、带宽、面积与位置）。 上述资源均为支撑泊松噪声限（Poisson noise limit）下峰参数估计精度相关研究而开发。