Titlebook: Intelligent Computing Theories and Applications; 8th International Co De-Shuang Huang,Jianhua Ma,M. Michael Gromiha Conference proceedings

–DOX

Knowledge Reduction Based on Evidence Reasoning Theory in Interval Ordered Information Systemsfields. In this paper, the basic concepts and properties of knowledge reduction based on evidence reasoning theory are discussed. Furthermore, the characterization and knowledge reduction approaches based on evidence reasoning theory are obtained.

消音器

輕信

Spatial-Based Feature for Locating Objectsion and recognition tasks. We develop a system that can recognize an object whose positional relation with another object is indicated verbally by a human. Experimental results using two image datasets prepared by the authors confirm the usefulness of the proposed feature.

Talkative

Stability of a Predator-Prey Model with Modified Holling-Type II Functional Responsens the cross-diffusion can induce the Turing instability of the uniform equilibrium, which is stable for the kinetic system and for the self-diffusion reaction system. Also, the numerical simulation is given in this paper, and verifying the result of the paper is correct.

Nomadic

鎮(zhèn)壓

放棄

Mass Diagnosis in Mammography with Mutual Information Based Feature Selection and Support Vector Maction. Based on the initial contour guided by radiologist, level set algorithm is used to deform the contour and achieves the final segmentation. Morphological features are extracted from the boundary of segmented regions. Then, important features are extracted based on mutual information criterion.

Amenable

Mean Square Exponential Stability of Hybrid Neural Networks with Uncertain Switching Probabilitiesin switching probabilities. The Markovian jumping recurrent neural networks under consideration involve parameter uncertainties in the mode transition rate matrix. By employing a Lyapunov functional, a linear matrix inequality (LMI) approach is developed to establish an easy-totest and delay-indepen

Mutter

Time-Varying Neurocomputing: An Iterative Learning Perspectivee learning is applied for the network training, and a modified iterative learning least squares algorithm is presented. Under the assumption of bounded input signals, convergence results of the proposed learning algorithm are given. In order to realize periodic mappings, periodic neural networks are

橡子

Knowledge Reduction Based on Evidence Reasoning Theory in Interval Ordered Information Systemsfields. In this paper, the basic concepts and properties of knowledge reduction based on evidence reasoning theory are discussed. Furthermore, the characterization and knowledge reduction approaches based on evidence reasoning theory are obtained.