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Neutral learning of constrained nonlinear transformations

https://doi.org/10.1109/2.30722
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Outgoing claims: the papers this work cites, builds on, or argues with.

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Self-Organizing Neuromorphic Architecture for Manipulator Inverse Kinematics
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Neural-space generalization of a topological transformation
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Terminal attractors for addressable memory in neural networks
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The least constraint principle for learning in neurodynamics
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Programming a massively parallel, computation universal system: Static behavior
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Neurons with graded response have collective computational properties like those of two-state neurons.
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Generalization of back-propagation to recurrent neural networks
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Solution to the inverse kinematics problem in robotics by neural networks
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A complete generalized solution to the inverse kinematics of robots
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Introduction to robotics: Mechanics and control
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Uncertainty Analysis of Time-Dependent Nonlinear Systems: Theory and Application to Transient Thermal Hydraulics
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Parallel Distributed Processing

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