• It stems from the concept of instantaneous frequency, and it can describe accurately the local properties of dynamic data in the time-frequency plane.

    该方法源于瞬时频率的概念,它能把动态信号的局部特征正确地在时频域内予以描述。

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  • The results of the simulation and real examples demonstrate that this new kernel function can remove the interference terms effectively and enhance the resolution of time-frequency plane.

    仿真和实例分析表明:动态核函数能很好地去除交叉干扰项,提高分辨率,同时又证明了该方法的实用性和有效性。

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  • The concept of local energy in time-frequency plane, based on local wave theory, is defined. Then a new feature extraction method based on the local energy in time-frequency plane is given.

    在局域波理论的基础上,引入了时频局部能量的概念,进而提出了一种基于时频局部能量的特征提取方法。

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  • This method is able to estimate precisely the initial Doppler frequency and the Doppler centroid, and to distinguish between multiple targets lying in the same line in the time-frequency plane.

    该方法能够以较高精度估计目标的多普勒起始频率和中心频率,并能分辨在时频平面位于同一直线的多个目标。

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  • "Modulation domain" is a plane domain which is consisted of frequency and time signal axes.

    “调制域”是由信号的频率和时间两个轴构成的平面域。

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  • Modulation Domain and Pulse Analyzer(MDPA) analyzes signal using a plane domain which is consisted of frequency and time.

    调制域及脉冲分析仪利用时间和频率构成的平面域对信号进行分析。

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  • The L F signals are transformed by entropy based on wavelet packet algorithms for best basis selection, and the results are displayed in time- frequency space namely phase plane.

    该方法采用基于熵的小波包最佳基选取准则,对局部损伤信号进行自适应小波包分解,将分解结果显示于时—频空间即相平面上。

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  • The methods of time frequency analysis include linear, quadratic and adaptive methods. They provide effective tools for analyzing signal time varying spectrum in time frequency plane.

    时频分析方法分为线性、二次型和自适应等多种方法,它们提供了在时频二维平面上,分析信号时变功率谱的有效手段。

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  • By using the plane wave expansion and finite-different time-domain (FDTD) methods, we can find a larger absolute band gap in the low and high frequency.

    通过运用平面波展开方法以及有限差分时域(FDTD)方法进行分析,可以明显地发现,在低频和高频区域增大了光子晶体的光子禁带。

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  • Due to the good localization feature of the wavelet transform both in time plane and in frequency plane, a wavelet-based de-noise method is presented for extracting EPs in single trails.

    由于小波变换在时域和频域上都具有良好的局部化特性,基于小波变换的去噪方法,可以达到从单次样本中提取视觉诱发电位的目的。

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  • Due to the good localization feature of the wavelet transform both in time plane and in frequency plane, we present a wavelet-based denoising method for extracting EPs in single trails.

    由于小波变换在时域和频域上都具有良好的局部化特性,本文提出了一种基于小波变换的去噪方法,以期达到从单次样本中提取视觉诱发电位的目的。

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  • Due to the good localization feature of the wavelet transform both in time plane and in frequency plane, we present a wavelet-based denoising method for extracting EPs in single trails.

    由于小波变换在时域和频域上都具有良好的局部化特性,本文提出了一种基于小波变换的去噪方法,以期达到从单次样本中提取视觉诱发电位的目的。

    youdao

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