Echo State Network

Echo State Network

Echo State Networks are an instance of a general concept of Reservoir Computing. By incorporating the benefits of RNNs and not dealing with vanishing gradient problems, ESNs (1) assign random weights once initially, (2) feed training inputs, (3) linear regression comparison between target outputs and captured reservoir, (4) output weights are used as novel inputs. The theory behind is that random connections allow previous states to “echo” so that similar inputs will start to follow a predicted activation trajectory.

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