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。由于这些方法各有优缺点，因此在实际应用中应根据被分析信号的先验知识，对不同类型的信号采用不同的时频分析方法，以取得对时频分辨率的均衡，并尽可能抑制交叉项干扰。根据对一些典型信号模型，分别按不同的时频分析方法进行的分析，找出了适合于各信号模型的不同时频分析法。模拟分析结果证明，对于时频汇聚性能较好的高斯类信号和跳频信号，采用自适应方法可以取得较好的分析效果；而对于频率随时间变化较大的调频类信号，则采用STFT或WVD效果较好。同时还讨论了时频分析方法在图象分析与处理中的应用。

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. Each of them possesses its special advantages as well as disadvantages. Therefore, in practical applications, to make a balance in time and frequency resolution and to reduce cross term interference, different methods should be employed to deal with different kinds of signals in terms of the signals' previous knowledge. In this paper, we analyzed some typical signal models via using different time frequency analysis methods and found some effective methods that are suitable for these models. For examples, adaptive method is suitable for analyzing Gaussian like or frequency hopping signals, but STFT or WVD is suitable for chirp like signals. We also discussed the applications of these methods on image analysis and processing.