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(A recurrently connected neural network with iterative activation update. A noisy initial pattern (of neural activity) will converge to one of a set of template patterns that is stored in the network by its weighted connections. Because of this property it is also a model of Associative Memory. The Continuous Attractor Network uses continuous activation values (~ firing rates), while the Binary Attractor Network uses {0,1} or {-1,1} as possible neuronal activations.)
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