Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  present a technique to iteratively optimize poles of a recursive digital filter in parallel form. Only exposing the poles as the variables to optimize,  employ a linearly constrained gradient descent routine in which the numerical estimation of the error gradient involves first obtaining the zeros by projecting the target response over a basis of responses defined by the pole positions at a given step. Example fits are presented for exponentially decaying white noise and measured violin radiativity filters.
['Esteban Maestre', 'Gary P. Scavone', 'Julius O. Smith']
I am writing a research paper on a idea Design of Recursive Digital Filters in Parallel Form by Linearly Constrained Pole Optimization
[{"from": "human", "value": "I am writing a research paper on a idea Design of Recursive Digital Filters in Parallel Form by Linearly Constrained Pole Optimization"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  present a technique to iteratively optimize poles of a recursive digital filter in parallel form. Only exposing the poles as the variables to optimize,  employ a linearly constrained gradient descent routine in which the numerical estimation of the error gradient involves first obtaining the zeros by projecting the target response over a basis of responses defined by the pole positions at a given step. Example fits are presented for exponentially decaying white noise and measured violin radiativity filters."}]