Fuzziness must be considered in systems where available information is uncertain. A model of such a vague phenomenon might be represented as a fuzzy system equation which can be described by the fuzzy functions defined by Zadeh’s extension principle. In this paper, we incorporate the concept of fuzzy set theory into the support vector machine (SVM). This integration preserves the benefits of SV...

This paper presents a fault detection, diagnosis, and reconfiguration method based on support vector machines. This method is appropriate for certain or predetermined faults and involves a fault detection and diagnosis unit and an online controller selection type reconfiguration mechanism. In this method, when a fault is detected and diagnosed by the fault detection and diagnosis unit, a suitab...

Because the SVM (support vector machine) classifies data with the widest symmetric margin to decrease the probability of the test error, modern fuzzy systems use SVM to tune the parameters of fuzzy if-then rules. But, solving the SVM model is time-consuming. To overcome this disadvantage, we propose a rapid method to solve the robust SVM model and use it to tune the parameters of fuzzy if-then ...

Since compared with the Support Vector Machine (SVM), the Relevance Vector Machine (RVM) not only has the advantage of avoiding the overlearn which is the characteristic of the SVM, but also greatly reduces the amount of computation of the kernel function and avoids the defects of the SVM that the scarcity is not strong, the large amount of calculation as well as the kernel function must satisf...

Face recognition has a wide variety of applications such as in identity authentication, access control and surveillance. There has been a lot of research on face recognition over the past few years. They have mainly dealt with different aspects of face recognition. Algorithms have been proposed to recognize faces beyond variations in viewpoint, illumination, pose and expression. This has led to...

Access control is an important issue in information security. It is a necessary mechanism for protecting data in a computer system. In this paper, we apply support vector machines to construct an access control system. The security management framework is a pattern classification system using well trained support vector machines. The proposed system can not only be applied to broad access polic...

The use of spatial covariance matrix as feature is investigated for motor imagery EEG-based classification. A new kernel is derived by establishing a connection with the Riemannian geometry of symmetric positive definite matrices. Different kernels are tested, in combination with support vector machines, on a past BCI competition dataset. We demonstrate that this new approach outperforms signif...