The purpose of this research is to develop effective machine learning or data mining techniques based on flexible neural tree FNT. Based on the pre-defined instruction/operator se...
Many complex control problems require sophisticated solutions that are not amenable to traditional controller design. Not only is it difficult to model real world systems, but oft...
Recently, manifold learning has been widely exploited in pattern recognition, data analysis, and machine learning. This paper presents a novel framework, called Riemannian manifold...
Many combinatorial optimization problems in biosequence analysis are solved via dynamic programming. To increase programming productivity and program reliability, a domain specifi...
Blind inversion of a linear and instantaneous mixture of source signals is a problem often encountered in many signal processing applications. Efficient FastICA (EFICA) offers an ...