Many problems in practically all fields of science, engineering and technology involve global optimization. It becomes more and more important to develop the efficient global opti...
Multi-valued and universal binary neurons (MVN and UBN) are the neural processing elements with the complex-valued weights and high functionality. It is possible to implement an a...
Abstract Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. A...
In this paper, we develop a theoretical understanding of multi-sensory knowledge and user context and their interrelationships. This is used to develop a generic representation fr...
In this paper, two modified constrained learning algorithms are proposed to obtain better generalization performance and faster convergence rate. The additional cost terms of the ...