Russian Federation
In this study, a multispectral one-dimensional modeling method based on a one-dimensional Gaussian model is proposed. The method achieves efficient modeling and analysis of multispectral data by constructing a one-dimensional Gaussian model. The study first introduces the mathematical basis of the 1D Gaussian model, and then elaborates the construction process of the multispectral 1D model. Through experimental validation, the method performs well in spectral feature extraction and data dimensionality reduction, providing a new idea for multispectral data analysis. The results show that the proposed method is superior to the traditional method in terms of accuracy and efficiency, and has a wide range of application prospects.
1D Gaussian model; multispectral analysis; 1D modeling; feature extraction; data dimensionality reduction
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