Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: An analytical form of the instantaneous frequency law (IFL) is very important when the physical parameters have to be evaluated from the time-frequency content of a signal. Generally, the analyzed signals are composed of several time-frequency components characterized by various nonlinear IFL. To deal with such signals,  propose a new method based on the warping operators (WO) and on the complex time distribution (CTD). Using parallel structures composed of several WO, some time-frequency components of the analyzed signal are linearized. This linearization is highlighted by using the CTD which considerably reduces the artefacts due to the complexity of the analyzed signal. This leads to an accurate estimation process, illustrated and justified by numerical and real examples.
['Cornel Ioana', 'Srdjan Stankovic', 'André Quinquis', 'LJubisa Stankovic']
I am writing a research paper on a idea Modelling of signal's time-frequency content using warped complex-time distributions
[{"from": "human", "value": "I am writing a research paper on a idea Modelling of signal's time-frequency content using warped complex-time distributions"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: An analytical form of the instantaneous frequency law (IFL) is very important when the physical parameters have to be evaluated from the time-frequency content of a signal. Generally, the analyzed signals are composed of several time-frequency components characterized by various nonlinear IFL. To deal with such signals,  propose a new method based on the warping operators (WO) and on the complex time distribution (CTD). Using parallel structures composed of several WO, some time-frequency components of the analyzed signal are linearized. This linearization is highlighted by using the CTD which considerably reduces the artefacts due to the complexity of the analyzed signal. This leads to an accurate estimation process, illustrated and justified by numerical and real examples."}]