To improve the accuracy and speed in cycle-accurate power estimation, this paper uses multiple dimensional coefficients to build a Bayesian inference dynamic power model. By analyzing the power distribution and intern...To improve the accuracy and speed in cycle-accurate power estimation, this paper uses multiple dimensional coefficients to build a Bayesian inference dynamic power model. By analyzing the power distribution and internal node state, we find the deficiency of only using port information. Then, we define the gate level number computing method and the concept of slice, and propose using slice analysis to distill switching density as coefficients in a special circuit stage and participate in Bayesian inference with port information. Experiments show that this method can reduce the power-per-cycle estimation error by 21.9% and the root mean square error by 25.0% compared with the original model, and maintain a 700 ＋ speedup compared with the existing gate-level power analysis technique.展开更多
The original temporal clustering analysis (OTCA) is an effective technique for obtaining brain activation maps when the timing and location of the activation are completely unknown, but its deficiency of sensitivity i...The original temporal clustering analysis (OTCA) is an effective technique for obtaining brain activation maps when the timing and location of the activation are completely unknown, but its deficiency of sensitivity is exposed in processing brain activation signal which is relatively weak. The time slice analysis method based on OTCA is proposed considering the weakness of the functional magnetic resonance imaging (fMRI) signal of the rat model. By dividing the stimulation period into several time slices and analyzing each slice to detect the activated pixels respectively after the background removal, the sensitivity is significantly improved. The inhibitory response in the hypothalamus after glucose loading is detected successfully with this method in the experiment on rat. Combined with the OTCA method, the time slice analysis method based on OTCA is effective on detecting when, where and which type of response will happen after stimulation, even if the fMRI signal is weak.展开更多
The application ofbispectrum analysis in fault diagnosis o f gears is studied in this paper. Bispectrum analysis is capable of removing Gau ssian or symmetric non-Gaussian noise and providing more information than pow...The application ofbispectrum analysis in fault diagnosis o f gears is studied in this paper. Bispectrum analysis is capable of removing Gau ssian or symmetric non-Gaussian noise and providing more information than power spectrum analysis.The results of the research show that normal gear sig nals, cracked gear signals and broken gear signals can be easily distinguished b y using bispectrumas the signal features. The bispectrum diagonal slice B_x(ω_1,ω_2) can be used to identifythe gear condition automatically.展开更多
文摘To improve the accuracy and speed in cycle-accurate power estimation, this paper uses multiple dimensional coefficients to build a Bayesian inference dynamic power model. By analyzing the power distribution and internal node state, we find the deficiency of only using port information. Then, we define the gate level number computing method and the concept of slice, and propose using slice analysis to distill switching density as coefficients in a special circuit stage and participate in Bayesian inference with port information. Experiments show that this method can reduce the power-per-cycle estimation error by 21.9% and the root mean square error by 25.0% compared with the original model, and maintain a 700 ＋ speedup compared with the existing gate-level power analysis technique.
基金the National Natural Science Foundation of China (30370432)
文摘The original temporal clustering analysis (OTCA) is an effective technique for obtaining brain activation maps when the timing and location of the activation are completely unknown, but its deficiency of sensitivity is exposed in processing brain activation signal which is relatively weak. The time slice analysis method based on OTCA is proposed considering the weakness of the functional magnetic resonance imaging (fMRI) signal of the rat model. By dividing the stimulation period into several time slices and analyzing each slice to detect the activated pixels respectively after the background removal, the sensitivity is significantly improved. The inhibitory response in the hypothalamus after glucose loading is detected successfully with this method in the experiment on rat. Combined with the OTCA method, the time slice analysis method based on OTCA is effective on detecting when, where and which type of response will happen after stimulation, even if the fMRI signal is weak.
文摘The application ofbispectrum analysis in fault diagnosis o f gears is studied in this paper. Bispectrum analysis is capable of removing Gau ssian or symmetric non-Gaussian noise and providing more information than power spectrum analysis.The results of the research show that normal gear sig nals, cracked gear signals and broken gear signals can be easily distinguished b y using bispectrumas the signal features. The bispectrum diagonal slice B_x(ω_1,ω_2) can be used to identifythe gear condition automatically.
文摘Microscopic imaging based on second-harmonic generation has been proving to be a powerful tool for biomedical studies, especially in that tissues with
