Neural Computation and Self-organizing Maps: An Introduction |
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adaptation step algorithm assigned auditory cortex average biological Br(t brain Chapter chosen configuration 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 image plane initial values input pattern input signals input stimuli Jacobian matrices joint angles Kohonen Kohonen's model lattice points layer learning algorithm learning steps linear mathematical matrix minimization motor neighborhood neighbors neural network neural units neurons obtain one-dimensional orientation output values parameters perceptron plane of camera positioning error principal curve problem pseudoinverse random receptive fields region retina robot arm saccades Schulten self-organizing maps sensory shows simulation solution space spatial stimulus subnet superior colliculus synaptic strengths target task three-dimensional tion touch receptors training pairs traveling salesman problem two-dimensional vector quantization visual visual cortex