کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
438783 690326 2006 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A concise functional neural network computing the largest modulus eigenvalues and their corresponding eigenvectors of a real skew matrix
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
A concise functional neural network computing the largest modulus eigenvalues and their corresponding eigenvectors of a real skew matrix
چکیده انگلیسی

Quick extraction of the largest modulus eigenvalues of a real antisymmetric matrix is important for some engineering applications. As neural network runs in concurrent and asynchronous manner in essence, using it to complete this calculation can achieve high speed. This paper introduces a concise functional neural network (FNN), which can be equivalently transformed into a complex differential equation, to do this work. After obtaining the analytic solution of the equation, the convergence behaviors of this FNN are discussed. Simulation result indicates that with general initial complex values, the network will converge to the complex eigenvector which corresponds to the eigenvalue whose imaginary part is positive, and modulus is the largest of all eigenvalues. Comparing with other neural networks designed for the like aim, this network is applicable to real skew matrices.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Theoretical Computer Science - Volume 367, Issue 3, 1 December 2006, Pages 273-285