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Post-processing methods for delay embedding and feature scaling of reservoir computers

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Abstract Reservoir computing is a machine learning method that is well-suited for complex time series prediction tasks. Both delay embedding and the projection of input data into a higher-dimensional space play important roles in enabling accurate predictions. We establish simple post-processing methods that train on past node states at uniformly or randomly-delayed timeshifts. https://www.herbsdailyes.shop/product-category/male-contraceptives/
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