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Gradient-Based Learning Algorithms for Recurrent Networks and Their Computational Complexity

, and . Back-propagation:Theory, Architectures and Applications, Lawrence Erlbaum Associates, Hillsdale, NJ, USA, (1995)

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Recurrent Network Model of Short-Term Active Memory. Neural Computation, 3 (2): 179--193 (1991)Gradient-based learning algorithms for recurrent networks and their computational complexity, and . Back-propagation: Theory, Architectures and Applications, Hillsdale, NJ: Erlbaum, (1994)A learning algorithm for continually running fully recurrent networks, and . Neural Computation, 1 (2): 270--280 (1989)Gradient-Based Learning Algorithms for Recurrent Networks and Their Computational Complexity, and . Back-propagation:Theory, Architectures and Applications, Lawrence Erlbaum Associates, Hillsdale, NJ, USA, (1995)A Subgrouping Strategy that Reduces Learning Complexity and Speeds Up Learning in Recurrent Networks. Neural Computation, 1 (4): 552--558 (1989)Learning sequential structures with the real-time recurrent learning algorithm, and . International Journal of Neural Systems, (1990)Gradient-Based Learning Algorithms for Recurrent Networks and Their Computatinal Complexity, and . Back-propagation:Theory, Architectures and Applications, Lawrence Erlbaum, Hillsdale, NJ: Erlbaum, (1995)A learning algorithm for continually running fully recurrent networks, and . ICS Report 8805. Univ. of California, San Diego, La Jolla, (1988)Unsupervised Discovery of Speech Segments Using Recurrent Networks, and . Proc. of the 1990 Connectionist Models Summer School, page 52--61. Morgan Kaufmann, (1990)Learning sequential structures with the real-time recurrent learning algorithm, and . International Journal of Neural Systems, 1 (2): 125--131 (1989)