Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Bilinear time-frequency distributions (TFDs) are developed to represent time-varying signal jointly in time and frequency representation (TFR). Since the TFDs offer good time and frequency resolution, they are appropriate to analyze por quality signals that consist of magnitude variation and multiple frequencies. Hover, the TFD suffer from cross-terms interferences due to their bilinear structures. , smooth-windod Wigner-Ville distribution (SWWVD) is used to analyze por quality signals. The por quality signals are sll, sag, interruption, harmonic, interharmonic and transient. To get accurate TFR, the parameters of the separable kernel are estimated from the signal. A set of performance measures is defined and used to compare the TFR for various kernel parameters. The comparison shows that signals with different parameters require different kernel settings to get the optimal TFR.
['Abdul Rahim Abdullah', "Ahmad Zuri Sha'ameri"]
I am writing a research paper on a idea Power quality analysis using smooth-windowed wigner-ville distribution
[{"from": "human", "value": "I am writing a research paper on a idea Power quality analysis using smooth-windowed wigner-ville distribution"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Bilinear time-frequency distributions (TFDs) are developed to represent time-varying signal jointly in time and frequency representation (TFR). Since the TFDs offer good time and frequency resolution, they are appropriate to analyze por quality signals that consist of magnitude variation and multiple frequencies. Hover, the TFD suffer from cross-terms interferences due to their bilinear structures. , smooth-windod Wigner-Ville distribution (SWWVD) is used to analyze por quality signals. The por quality signals are sll, sag, interruption, harmonic, interharmonic and transient. To get accurate TFR, the parameters of the separable kernel are estimated from the signal. A set of performance measures is defined and used to compare the TFR for various kernel parameters. The comparison shows that signals with different parameters require different kernel settings to get the optimal TFR."}]