کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
409175 | 679057 | 2008 | 5 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A neural networks learning algorithm for minor component analysis and its convergence analysis
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: A neural networks learning algorithm for minor component analysis and its convergence analysis A neural networks learning algorithm for minor component analysis and its convergence analysis](/preview/png/409175.png)
چکیده انگلیسی
The eigenvector associated with the smallest eigenvalue of the autocorrelation matrix of input signals is called minor component. Minor component analysis (MCA) is a statistical approach for extracting minor component from input signals and has been applied in many fields of signal processing and data analysis. In this letter, we propose a neural networks learning algorithm for estimating adaptively minor component from input signals. Dynamics of the proposed algorithm are analyzed via a deterministic discrete time (DDT) method. Some sufficient conditions are obtained to guarantee convergence of the proposed algorithm.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 71, Issues 7–9, March 2008, Pages 1748–1752
Journal: Neurocomputing - Volume 71, Issues 7–9, March 2008, Pages 1748–1752
نویسندگان
Dezhong Peng, Zhang Yi, JianCheng Lv, Yong Xiang,