Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In the Echo State Networks (ESN) and, more generally, Reservoir Computing paradigms (a recent approach to recurrent neural networks), linear readout ights, i.e., linear output ights, are the only ones actually learned under training. The standard approach for this is SVD-based pseudo-inverse linear regression. Here it will be compared with two ll known on-line filters, Least Minimum Squares (LMS) and Recursive Least Squares (RLS). As  shall illustrate, while LMS performance is not satisfactory, RLS can be a good on-line alternative that may deserve further attention.
['Carlos M. Alaíz', 'José R. Dorronsoro']
I am writing a research paper on a idea On the learning of ESN linear readouts
[{"from": "human", "value": "I am writing a research paper on a idea On the learning of ESN linear readouts"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In the Echo State Networks (ESN) and, more generally, Reservoir Computing paradigms (a recent approach to recurrent neural networks), linear readout ights, i.e., linear output ights, are the only ones actually learned under training. The standard approach for this is SVD-based pseudo-inverse linear regression. Here it will be compared with two ll known on-line filters, Least Minimum Squares (LMS) and Recursive Least Squares (RLS). As  shall illustrate, while LMS performance is not satisfactory, RLS can be a good on-line alternative that may deserve further attention."}]