Dynamic recurrent neural networks
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[1] A. E. Bryson,et al. A Steepest-Ascent Method for Solving Optimum Programming Problems , 1962 .
[2] P. Werbos,et al. Beyond Regression : "New Tools for Prediction and Analysis in the Behavioral Sciences , 1974 .
[3] Stephen Grossberg,et al. Absolute stability of global pattern formation and parallel memory storage by competitive neural networks , 1983, IEEE Transactions on Systems, Man, and Cybernetics.
[4] Geoffrey E. Hinton,et al. OPTIMAL PERCEPTUAL INFERENCE , 1983 .
[5] C. D. Gelatt,et al. Optimization by Simulated Annealing , 1983, Science.
[6] Geoffrey E. Hinton,et al. A Learning Algorithm for Boltzmann Machines , 1985, Cogn. Sci..
[7] Geoffrey E. Hinton,et al. Learning internal representations by error propagation , 1986 .
[8] J. M. Sanz-Serna,et al. On simple moving grid methods for one-dimensional evolutionary partial differential equations , 1988 .
[9] Carsten Peterson,et al. A Mean Field Theory Learning Algorithm for Neural Networks , 1987, Complex Syst..
[10] Pineda,et al. Generalization of back-propagation to recurrent neural networks. , 1987, Physical review letters.
[11] A. Lapedes,et al. Nonlinear signal processing using neural networks: Prediction and system modelling , 1987 .
[12] James P. Crutchfield,et al. Equations of Motion from a Data Series , 1987, Complex Syst..
[13] Amir F. Atiya. Learning on a General Network , 1987, NIPS.
[14] Anthony J. Robinson,et al. Static and Dynamic Error Propagation Networks with Application to Speech Coding , 1987, NIPS.
[15] W. Freeman,et al. How brains make chaos in order to make sense of the world , 1987, Behavioral and Brain Sciences.
[16] Steven J. Nowlan,et al. Gain Variation in Recurrent Error Propagation Networks , 1988, Complex Syst..
[17] PAUL J. WERBOS,et al. Generalization of backpropagation with application to a recurrent gas market model , 1988, Neural Networks.
[18] Bernard Widrow,et al. Adaptive switching circuits , 1988 .
[19] Robert A. Jacobs,et al. Increased rates of convergence through learning rate adaptation , 1987, Neural Networks.
[20] Patrice Y. Simard,et al. Fixed Point Analysis for Recurrent Networks , 1988, NIPS.
[21] M. Gherrity,et al. A learning algorithm for analog, fully recurrent neural networks , 1989, International 1989 Joint Conference on Neural Networks.
[22] Geoffrey E. Hinton. Deterministic Boltzmann Learning Performs Steepest Descent in Weight-Space , 1989, Neural Computation.
[23] Barak A. Pearlmutter. Learning State Space Trajectories in Recurrent Neural Networks , 1989, Neural Computation.
[24] Terrence J. Sejnowski,et al. Learning to Solve Random-Dot Stereograms of Dense and Transparent Surfaces with Recurrent Backpropagation , 1989 .
[25] Geoffrey E. Hinton. Learning distributed representations of concepts. , 1989 .
[26] M. Gori,et al. BPS: a learning algorithm for capturing the dynamic nature of speech , 1989, International 1989 Joint Conference on Neural Networks.
[27] David Zipser,et al. Subgrouping Reduces Complexity and Speeds Up Learning in Recurrent Networks , 1989, NIPS.
[28] Richard Rohwer,et al. The "Moving Targets" Training Algorithm , 1989, NIPS.
[29] James L. McClelland,et al. Finite State Automata and Simple Recurrent Networks , 1989, Neural Computation.
[30] Geoffrey E. Hinton,et al. Phoneme recognition using time-delay neural networks , 1989, IEEE Trans. Acoust. Speech Signal Process..
[31] Ronald J. Williams,et al. A Learning Algorithm for Continually Running Fully Recurrent Neural Networks , 1989, Neural Computation.
[32] Robert B. Allen,et al. Learning of stable states in stochastic asymmetric networks , 1990, IEEE Trans. Neural Networks.
[33] Terrence J. Sejnowski,et al. Faster Learning for Dynamic Recurrent Backpropagation , 1990, Neural Computation.
[34] W. Kristan,et al. Distributed processing of sensory information in the leech. I. Input- output relations of the local bending reflex , 1990, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[35] Jeffrey L. Elman,et al. Finding Structure in Time , 1990, Cogn. Sci..
[36] S. Renals,et al. A study of network dynamics , 1990 .
[37] L. B. Almeida. A learning rule for asynchronous perceptrons with feedback in a combinatorial environment , 1990 .
[38] Patrice Y. Simard,et al. Shaping the State Space Landscape in Recurrent Networks , 1990, NIPS.
[39] S. Lockery,et al. Distributed processing of sensory information in the leech. II. Identification of interneurons contributing to the local bending reflex , 1990, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[40] Michael I. Jordan. Attractor dynamics and parallelism in a connectionist sequential machine , 1990 .
[41] Geoffrey E. Hinton,et al. A time-delay neural network architecture for isolated word recognition , 1990, Neural Networks.
[42] Terrence J. Sejnowski,et al. A Dynamic Neural Network Model of Sensorimotor Transformations in the Leech , 1990, Neural Computation.
[43] J. Barhen,et al. Adjoint-operators and non-adiabatic learning algorithms in neural networks , 1991 .
[44] Geoffrey E. Hinton,et al. Deterministic Boltzmann Learning in Networks with Asymmetric Connectivity , 1991 .