Rough - set - based fuzzy - neural - network system for taste signal identification 粗糙集模糊神經(jīng)網(wǎng)絡(luò)味覺信號識別系統(tǒng)
The core problem of this thesis is to study the different acoustic signal identification methods 本論文的核心就是研究不同地聲目標識別方法。
Aimed at a great deal of components submitted to the skewness distribution during the mixed signal identification , a new improved independent component analysis algorithm is proposed to deal with this kind of signals 摘要針對實際混合信號中許多分量具有偏態(tài)分布的特點,提出了一種用于該類混合信號的新的獨立分量分析算法。
Furthermore , the influencies of wavelet parameters to signal identification and signal parameter estimation have been systematically studied , and the results have been adopted to outperform the above procedures 為了更好的識別與提取信號參數(shù),作者還進行了大量的公式推導與實驗仿真研究了小波參數(shù)的變化對信號處理的影響。