Title :
Upper-Triangulization of Non-Symmetric Matrices Using Sanger´s Type Learning Systems
Author :
Hasan, Mohammed A.
Author_Institution :
Dept. of Electr. & Comput. Eng., Minnesota Univ., Duluth, MN
Abstract :
New minor and principal component flows are derived and analyzed in terms of global stability and properties of the limiting solutions. These systems which are of Sanger´s type are specifically explored in terms of their applicability to symmetric and non-symmetric matrices. Analytical proofs of global stability and conditions under which the limiting solutions upper-triangulize a given matrix are given.
Keywords :
matrix algebra; principal component analysis; stability; Lyapunov stability; Sanger type learning systems; global convergence; global stability; minor components; nonsymmetric matrices; principal components; symmetric matrices; upper-triangulization; Eigenvalues and eigenfunctions; Lagrangian functions; Learning systems; Lyapunov method; Matrix converters; Principal component analysis; Stability analysis; Symmetric matrices; Liapunov stability; MCA/PCA for non-symmetric matrices; Oja´s learning rule; global convergence; minor components; principal components;
Conference_Titel :
Circuits and Systems, 2007. ISCAS 2007. IEEE International Symposium on
Conference_Location :
New Orleans, LA
Print_ISBN :
1-4244-0920-9
Electronic_ISBN :
1-4244-0921-7
DOI :
10.1109/ISCAS.2007.378140
