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In view of the current situation of the computer equipment in our library, use the fuzzy AHP method to comprehensive evaluate the advanced degree of computer equipment in our library, draw a conclusion: the advanced degree of computer equipment in our library is in the medium level, and propose the corresponding solutions to improve the situation.
Speaker recognition system needs sufficient data to discriminate speaker well. In case of limited data, especially when the amount of available training and testing data were few seconds, the system performance decreased significantly. It proposed a discriminative weighted fuzzy kernel vector quantization method for speaker identification with limited data. By non-linear mapping, it quantized the...
Aiming at the knowledge mining from fuzzy and uncertain information, the definition mode and properties of the fuzzy formal context are discussed in the paper. The method of constructing the fuzzy concept lattice of the fuzzy formal context is proposed, in that the definition of fuzzy product concept is the core: the intents of two concepts are combined to form the intent of the product concept; using...
In case of limited data, the system performance of speaker recognition decreased significantly. To resolve this problem, it designed fuzzy kernel entropy vector quantization with sectional set to train speakers' models and make identification decision in high-dimensional feature space. Entropy function can make the algorithm have clear physical meaning and avoid the unsuitable choose of fuzzy weighted...
When the amount of available training and testing data will be few seconds, the number of feature vectors we obtain are less which are insufficient to model and discriminate speaker well. It presented a new method for speaker recognition with short utterances. By non-linear mapping, it used the sectional set fuzzy Vector Quantization with Lp norm to form speaker's model in the high-dimensional feature...
The traditional training methods of Gaussian mixture model (GMM) are sensitive to the initial parameters, and when the training data is limited, it has weak generalization. To resolve theses problems, it proposed a novel GMM optimization method. It used the fuzzy expectation maximization approach and the niche technique to form new hybrid architecture, which can reduce the possibility of premature...
Based on the discussion on the evaluation index of University Libraries Service Level, the essay proposed AGA-FAHP comprehensive evaluation method, expounded its advantages and method principle, analyzed the example and concluded that this method can efficiently and quickly evaluate the service level of University Library.
There are some weaknesses in the traditional safety evaluation methods, such as, slow reasoning, low accuracy and so on, so thinking of a variety of factors which affect gas safety, a gas safety evaluation index system is built, which focuses on the state of gas, mine ventilation, gas monitoring, safety management and kindling. Combining the fuzzy comprehensive evaluation method with gray correlation...
This study considers the problem of generating all minimal solutions of a system of fuzzy relational equations (FREs) with max-Archimedean t-norm composition. It defines the binding matrix of a system of FREs, and then shows that an irredundant covering of the binding matrix corresponds to a minimal solution of the FREs. Consequently, the problem of finding all minimal solutions of the FREs can be...
Fuzzy C-Means clustering is one of the most perfective and widely used algorithms based on objective function for unsupervised classification. Considering the spatial relationship of pixels when it is used in remote sensing imagery, Neighbor-based FCM algorithm is put forward with the method of modifying the value of fuzzy membership degrees with the neighbor information during the clustering iterations...
It proposed a fuzzy kernel vector quantization method for speaker recognition with little training data. By non-linear mapping, it quantized the input data in the high-dimensional feature space, and used the cluster centers to form the speaker's model. Because of the kernel method, it made the inherent speech features explored, and the dissimilarity among different speakers increased. Besides, it...
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