## Neural computation and self-organizing maps: an introduction |

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### Contents

Introduction and Overview | 7 |

Contemporary View of Brain Function | 15 |

Neural Network Models | 25 |

Copyright | |

12 other sections not shown

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### Common terms and phrases

adaptation step algorithm approximation assigned auditory cortex average biological brain Chapter chosen connected convergence coordinates correct corresponding cortical cylinder degrees of freedom denotes determined dimensional distribution elements end effector positions equation example excitation Figure fluctuations fovea frequency gradient descent gripper hand surface Hence hyperplane image plane initial values input pattern input signals input stimuli Jacobian matrices joint angles Kohonen's model lattice points layer learning algorithm learning steps linear Markov process mathematical matrix minimization motor neighborhood neighbors neural network neural units neurons nodes obtain one-dimensional orientation output values parameters perceptron plane of camera positioning error principal curve problem pseudoinverse random receptive fields region represents retina reward function robot arm saccades self-organizing maps sensory shows simulation solution space spatial stimulus subnet synaptic strengths task three-dimensional tion torque touch receptors training pairs traveling salesman problem two-dimensional vectors wr visual visual cortex