Numerical Analysis of the Diversity of Keyboard Instrument Playing Fingerings

Abstract

Abstract Fingering is the foundation of keyboard instrument performance and an important part of keyboard music, but few people pay attention to its development. The evolution from the early variety of playing fingerings to the thumb-centered five-fingerings is even less mentioned. At present, steganographic analysis mainly focuses on the diversity and high dimensionality of features. Faced with the emerging new steganography, it is difficult for a single feature to cover and express the influence of steganography process on the multi-dimensional distribution of images. Therefore, it is necessary to combine various features through certain methods to analyze the changes of image properties before and after steganography embedding in a larger range and more types. The experimental results show that the experimental comparison diagram of Comb-RichModel based on diversity features and other steganographic analysis algorithms can be seen by replacing filtering and adding SPAM features. Compared with numerical analysis, the detection accuracy of the Comb-RichModel with diversified features has been improved to some extent, and its detection performance has improved stably from low embedding rate to high embedding rate. It is proved that the numerical analysis can effectively analyze the diversity characteristics of keyboard instrument playing fingerings.