Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Fast and robust acoustic system identification is still a research topic of interest, because of the typically time-variant nature of acoustic systems and the natural performance limitation of electroacoustic measurement equipment. ,  propose NLMS-type adaptive identification with perfect-sep excitation. The perfect-sep is derived from the more general class of perfect sequences and, thus, it inherits periodicity and especially the desired decorrelation property known from perfect sequences. Moreover, the perfect-sep shows the desirable characteristics of spt sine signals regarding the immunity against non-linear loudspeaker distortions. On this basis,  first demonstrate the fast tracking ability of the perfect-sep NLMS algorithm via computer generated simulation of a time-variant acoustic system. Then, the robustness of the perfect-sep NLMS algorithm against non-linear characteristics of real measurements in a time-invariant case is presented. By finally addressing the measurement of quasi-continuous head-related impulse responses,  face the combined challenge of time-variant and possibly non-linear distorted acoustic system identification in a real application scenario and  can demonstrate the superiority of the perfect-sep NLMS algorithm.
['Christiane Antweiler', 'Aulis Telle', 'Peter Vary', 'Gerald Enzner']
I am writing a research paper on a idea Perfect-sweep NLMS for time-variant acoustic system identification
[{"from": "human", "value": "I am writing a research paper on a idea Perfect-sweep NLMS for time-variant acoustic system identification"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Fast and robust acoustic system identification is still a research topic of interest, because of the typically time-variant nature of acoustic systems and the natural performance limitation of electroacoustic measurement equipment. ,  propose NLMS-type adaptive identification with perfect-sep excitation. The perfect-sep is derived from the more general class of perfect sequences and, thus, it inherits periodicity and especially the desired decorrelation property known from perfect sequences. Moreover, the perfect-sep shows the desirable characteristics of spt sine signals regarding the immunity against non-linear loudspeaker distortions. On this basis,  first demonstrate the fast tracking ability of the perfect-sep NLMS algorithm via computer generated simulation of a time-variant acoustic system. Then, the robustness of the perfect-sep NLMS algorithm against non-linear characteristics of real measurements in a time-invariant case is presented. By finally addressing the measurement of quasi-continuous head-related impulse responses,  face the combined challenge of time-variant and possibly non-linear distorted acoustic system identification in a real application scenario and  can demonstrate the superiority of the perfect-sep NLMS algorithm."}]