论文标题
光谱图零的无监督分类
Unsupervised classification of the spectrogram zeros
论文作者
论文摘要
事实证明，频谱图的零是描述信号的时频结构的相关特征，该特征是由时间频平面中的组件之间的破坏性干扰起源的。在这项工作中，基于干扰生产它们的组件的性质，将这些零分类用于三种类型。与噪声辅助方法相呼应，根据添加独立的噪声实现来构建描述零的稳定性的2D直方图，提出了分类算法。从该直方图中提取的特征随后使用非监督聚类算法对零进行分类。还引入了基于频谱零分类的降解方法。为合成和真实信号提供了零分类的示例，以及通过另一种基于零的方法对拟议的denoise算法进行性能比较。
The zeros of the spectrogram have proven to be a relevant feature to describe the time-frequency structure of a signal, originated by the destructive interference between components in the time-frequency plane. In this work, a classification of these zeros in three types is introduced, based on the nature of the components that interfere to produce them. Echoing noise-assisted methods, a classification algorithm is proposed based on the addition of independent noise realizations to build a 2D histogram describing the stability of zeros. Features extracted from this histogram are later used to classify the zeros using a non-supervised clusterization algorithm. A denoising approach based on the classification of the spectrogram zeros is also introduced. Examples of the classification of zeros are given for synthetic and real signals, as well as a performance comparison of the proposed denoising algorithm with another zero-based approach.
