Title :
Spectral methods for testing membership in certain post classes and the class of forcing functions
Author :
Shmulevich, Ilya ; Lähdesmäki, Harri ; Egiazarian, Karen
Author_Institution :
Univ. of Texas M. D. Anderson Cancer Center, Houston, TX, USA
Abstract :
Forcing functions represent an important class of Boolean functions that have been extensively studied in the analysis of the dynamics of random Boolean networks as models of genetic regulatory systems. Several other so-called Post classes of Boolean functions are closely related to forcing functions and have been used in learning theory as well as in control systems. We develop novel spectral algorithms to test membership of a Boolean function in these classes. These algorithms are highly efficient and are essential in learning problems, especially in the context of genetic regulatory networks, where the same learning procedures are applied repeatedly.
Keywords :
Boolean functions; spectral analysis; stack filters; Boolean functions; forcing function; genetic regulatory systems; post class membership testing; random Boolean networks; spectral algorithm; Bioinformatics; Boolean functions; Cancer; Convergence; Digital filters; Genetics; Genomics; Nonlinear filters; Signal processing algorithms; Testing;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2003.821725