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The performance conditions of steam turbine regenerative system have important influence on the safety and economy of the units. It is of great significance to doing the research on the performance monitoring of the regenerative system to ensure the safe and economical operation of the whole coal-fired power plants. In view of the shortcomings of the complexity of traditional performance monitoring...
Every user has a distinct background and a specific goal when searching for information on the Web. The goal of Web search personalization is to tailor search results to a particular user based on that user's interests and preferences. This paper presents an approach of search engine optimization based on algorithm of BP neural networks aiming at meeting the increasing requirements of modern people...
Neural networks can easily fall into a local extremum and have slow convergence rate. Quantum Genetic Algorithm (QGA) has features of small population size and fast convergence. Based on the investigation of QGA, we propose a novel neural network model, Radial Basis Function (RBF) networks optimized by Quantum Genetic Algorithm (QGA-RBF model). Then we investigate the performance of the proposed QGA-RBF...
In this paper, an analog current mode implementation of a fully programmable Gaussian function generator (GFG) is presented. The subthreshold current mode circuits enable the design to operate at very low supply voltage and consume very little power. Translinear loop technique is used to generate high precision quadratic current and a single PMOS transistor is used to generate the Gaussian profile...
In this paper, a kind of improved method of diploid genetic algorithm (DGA) without considering the dominant and recessive of the allele is given directed at the disadvantages of DGA which are easy to fall into premature convergence and have low efficiency in late period local searching. Improved the genetic operation process by imitating the reproductive processes of diplont and adopting the process...
Fuzzy Integral is widely accepted and applied in multi-classifier fusion to express the importance of individual classifiers and the interaction among classifiers. In this fusion model, there are two keys to determine. One is determining the fuzzy measure. Many researchers have done much work and proposed many types of fuzzy measure and methods to determine fuzzy measures. Another is selecting from...
In order to choose the rotating machinery fault diagnosis characteristics accurately, in this paper, a kind of choice method of fault diagnosis characteristics was put forward based on the time domain statistical analysis. Through analysis the probability distribution of the time domain dimensionless characteristic parameters, choose the parameters witch is obviously different from others and used...
Quantum neural network (QNN) gives us some advantages unattainable by classical artificial neural network. A model of quantum neuron composed of quantum gates is described. A model of quantum back propagation neural network (QBPNN) based on the quantum neuron and its training algorithm is investigated. A novel approach toward speech enhancement which adopts QBPNN is proposed. For comparison, evaluations...
The key of advancing radial basis function neural network (RBFNN) is how to choose the data center and the number of cluster perfectly. In this paper fuzzy C-means clustering is used as K-means clustering ameliorated algorithm to determine the data center of RBF neural networks hidden nodes. Combined pseudo-inverse method RBF network model is constructed. Simulation test on the dimension predicting...
Quantum Neural Network (QNN), a burgeoning new field which integrates quantum computation with classical neural network, can improve the inadequacies of artificial neural network. A model of quantum neuron and Quantum Back Propagation (BP) Neural Network based on quantum neuron are investigated. A novel approach toward speech enhancement which adopts Quantum BP Neural Network is proposed. The numerical...
It has been shown that the fuzzy integral is an effective tool for the fusion of multiple classifiers. Of primary importance in the development of the system is the choice of the measure which embodies the importance of subsets of classifiers. In this paper we propose a method for a dynamic fuzzy measure which will change following the pattern to be classified (data dependent). This method uses the...
In this paper, an analog current mode implementation of a neuron circuit capable of performing real Gaussian neighborhood taper learning is presented. The neuron cell is compacted with a reusable multiplier that can function as squarer and multiplier for Euclidean and topological distances calculation as well as for Gaussian function characteristics with adjustable learning rate. A four-neuron self-organizing...
In this paper. the notion of vector-valued multi-resolution analysis is introduced and the definition of orthogonal vector-valued wavelets. A necessary and sufficient condition on the existence of orthogonal vector-valued wavelets is given by using paraunitary vector filter bank theory. A method for constructing a class of compactly supported orthogonal vector-valued wavelets is proposed.
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