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Access to learning for pupils with disabilities designing optimization neural network models with global convergence. The second section of this book looks at recent applications of recurrent neural networks. Problems dealing with trajectories, control systems, robotics, and language learning are included, along with an interesting use of recurrent neural networks in chaotic systems. 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We explain in detail the different steps in computing a language model based on a recurrent neural network. • We survey the applications and findings based on the current literature. ... We survey the methods for reducing computational complexity. Abstract. In this paper, we present a survey on the application of recurrent neural networks to ... 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Buy this book ... of mathematical tools relating to dynamical system theory which has tumed out to be very useful in enabling a rigorous analysis of RNNs. Show all. Table of contents (8 chapters) Introduction. Yi, Zhang (et al.) ... Network Theory and Applications Series ... Thus, RNNs have to their disposal, a huge set of mathematical tools relating to dynamical system theory which has tumed out to be very useful in enabling a rigorous analysis of RNNs. Keywords calculus cognition image processing linear optimization network networks neural networks pattern recognition Convergence Analysis of Adaptive Recurrent Neural Network. 6 Pages. Convergence Analysis of Adaptive Recurrent Neural Network. ... The stability analysis is presented to establish the convergence theory of the Back propagation algorithm based on the Lyapunov function. ... E. Zhu. 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