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Supplier selection in industry is a cross-functional, group decision-making problem, frequently solved by a non-programmed decision-making process, and involving long-term commitment for a company. During recent years, how to determine suitable suppliers in the supply chain has become a key strategic consideration. However, the nature of these decisions usually is complex and unstructured. Especially,...
In view of the great potential in parallel processing and ready implementation via hardware, neural networks are now often employed to solve online matrix algebraic problems. Recently, a special kind of recurrent neural network has been proposed by Zhang et al, which could be generalized to solving online Lyapunov equation with time-varying coefficient matrices. In comparison with gradient-based neural...
This paper presents a simplified primal-dual neural network based on linear variational inequalities (LVI) for online repetitive motion planning of PA10 robot manipulator. To do this, a drift-free criterion is exploited in the form of a quadratic function. In addition, the repetitive-motion-planning scheme could incorporate the joint limits and joint velocity limits simultaneously. Such a scheme is...
A new method is proposed in this paper to implement the high precision analog-to-digital converter (ADC) with low precision ADC based on two-stage conversion. Because the main error of ADC is non-linear, an algorithm using wavelet neural network for compensating error and non-linearity of ADC is proposed, which has faster speed quality convergence and higher precision than BP neural network. By studying...
Unlike traditional pattern classification, semi-supervised learning provides a novel technique to make use of both labeled and unlabeled data for improving the performance of classification. In general, there are two critical issues for semi-supervised learning of discriminative classifiers; i.e., how to create an initial classifier of a good generalization capability with the limited labeled data...
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