多维信息集成算法视角下的特征提取与波形匹配分析

Hong Zhang
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引用次数: 0

摘要

中国古典音乐作为中国文化情感体验的传承者,在大学生优秀传统文化教育中具有保存其气质的价值,使其具有时代价值。通过降维优化得到20维特征,然后通过离散小波变换提取第1到第4尺度的细节系数和第4尺度的近似系数作为频域特征,具有凝聚年轻人“向上”、“向善”的力量。我们设置,使用MDI算法和传统的线性拟合和指数拟合算法获得相应的T2心理特征定量图,并计算和显示噪声传播特性,这三种算法的蒙特卡罗方法是必不可少的,并选择作为所提出模型的核心。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Feature Extraction and Waveform Matching from the Perspective of Multi-Dimensional Information Integration Algorithm
Chinese classical music has the value of conserving its temperament in the excellent traditional Chinese culture education of college students, making it the value of the times as the inheritor of Chinese cultural emotional experience. The 20dimensional features are obtained by dimensionality reduction optimization, and then the detail coefficients from the first scale to the fourth scale and the approximation coefficients of the fourth scale are extracted as frequency domain features through discrete wavelet transform, which has the power to gather young people to “go up” and “to be kind”. We set, using MDI algorithm and conventional linear fitting and exponential fitting algorithms to obtain the corresponding quantitative map of T2 mental characteristics and calculate and display the noise propagation characteristics of the three algorithms by Monte Carlo method is essential and selected as the core of the proposed model.
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