Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: This communication is composed of two related parts. First  propose an approximation to the Maximum Likelihood estimator of the γ distribution parameters.  show that it leads to build an efficient estimator of a white Gaussian process variance by noting that γ distribution admits sufficient statistics. Second  describe an application of this result to a non-stationary signal spectrogram segmentation that  proposed recently. Examples of segmented spectrograms are presented on a synthetic signal and on an acoustical recording of a dolphin whistle.
['Cyril Hory', 'Nadine Martin']
I am writing a research paper on a idea Maximum likelihood noise estimation for spectrogram segmentation control
[{"from": "human", "value": "I am writing a research paper on a idea Maximum likelihood noise estimation for spectrogram segmentation control"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: This communication is composed of two related parts. First  propose an approximation to the Maximum Likelihood estimator of the \u03b3 distribution parameters.  show that it leads to build an efficient estimator of a white Gaussian process variance by noting that \u03b3 distribution admits sufficient statistics. Second  describe an application of this result to a non-stationary signal spectrogram segmentation that  proposed recently. Examples of segmented spectrograms are presented on a synthetic signal and on an acoustical recording of a dolphin whistle."}]