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A generalised fuzzy approach to statistical modelling techniques for pattern recognition is proposed in this paper. Fuzzy C-means (FCM) and fuzzy entropy (FE) techniques are combined into a generalised fuzzy technique and applied to third-order two-dimensional hidden Markov mode(2-D HMM). 2-D HMM is an extension of 1-D HMM to 2-D, it provides a reasonable statistical method to model matrix data. By...
This paper presents a novel approach to eliminate the effect of noisy samples from the learning step of support vector data description (SVDD) method. SVDD is a popular kernel method which tries to fit a hypersphere around the target object and can obtain more flexible and more accurate data descriptions by using proper kernel functions. Nonetheless, the SVDD could sometimes generate such a loose...
In the field of pattern recognition multiple classifier systems based on the combination of outputs from different classifiers have been proposed as a method of high performance classification systems. The objective of this work is to develop a fuzzy Gaussian classifier for combining multiple learners, we use a fuzzy Gaussian model to combine the outputs obtained from K-nearest neighbor classifier...
The driver emergency braking behavior to be distinguished and predicted exactly was difficult. In order to gain the testing data of driver emergency braking action, 7 professional drivers were selected and 3 scenes of driver braking behavior were designed and simulated by means of road test. And the testing data were captured by the data acquisition system with sensors. Utilizing relative fuzzy membership...
Fuzzy entropy of classification is presented along with a criterion of maximizing the first derivative of the entropy with respect to temperature to optimize the degree of fuzziness. Fuzzy entropy of classification is used to construct classification trees comprised of multivariate fuzzy rules. These systems are of great use to scientists because of their discernable mechanism of inference. By using...
Because of the excellent performance of the HMM (hidden Markov model), it has been widely used in pattern recognition. Due to the high false alarm rate in the classical intrusion detection system (IDS) based on HMM, a fuzzy approach for the HMM, called fuzzy hidden Markov models (FHMM) is proposed. it is introduced with the fuzzy logic to the HMM. The robustness and accurate rate of the IDS based...
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