核(代数)
参数化复杂度
时频分析
算法
时频表示法
数学
计算机科学
频域
信号处理
S变换
信号(编程语言)
数字信号处理
人工智能
滤波器(信号处理)
小波变换
数学分析
离散数学
计算机视觉
小波
小波包分解
程序设计语言
计算机硬件
作者
Yixin Yang,Zhike Peng,Xingjian Dong,W. M. Zhang,Guang Meng
标识
DOI:10.1109/tsp.2014.2314061
摘要
Interest in parameterized time-frequency analysis for non-stationary signal processing is increasing steadily. An important advantage of such analysis is to provide highly concentrated time-frequency representation with signal-dependent resolution. In this paper, a general scheme, named as general parameterized time-frequency transform (GPTF transform), is proposed for carrying out parameterized time-frequency analysis. The GPTF transform is defined by applying generalized kernel based rotation operator and shift operator. It provides the availability of a single generalized time-frequency transform for applications on signals of different natures. Furthermore, by replacing kernel function, it facilitates the implementation of various parameterized time - frequency transforms from the same standpoint. The desirable properties and the dual definition in the frequency domain of GPTF transform are also described in this paper. One of the advantages of the GPTF transform is that the generalized kernel can be customized to characterize the time - frequency signature of non-stationary signal. As different kernel formulation has bias toward the signal to be analyzed, a proper kernel is vital to the GPTF. Thus, several potential kernels are provided and discussed in this paper to develop the desired parameterized time - frequency transforms. In real applications, it is desired to identify proper kernel with respect to the considered signal. This motivates us to propose an effective method to identify the kernel for the GPTF.
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