重点探索了基于时基微扰的帧时移线性去相关法(TPM -FTS)和帧伸缩非线性去相关法(TPM - FEC)。
TPM-based frame time-shifting (TPM-FTS) linear method and TPM-based frame expanding-compressing (TPM-FEC) nonlinear method were mainly explored.
它的分解基是随动态信号波形的变化而变化 ，具有自调节自适应的特征 ，因此能在时频域内描述非平稳非线性信号的局部特性。
Since the decomposition bases can vary with the local features of dynamic signals, the method is adaptive , therefore, highly efficient for describing nonlinear and non?stationary signals.
它的分解基是随动态信号波形的变化而变化 ，具有自调节自适应的特征 ，因此能在时频域内描述非平稳非线性信号的局部特性。
Since the decomposition bases can vary with the local features of dynamic signals, the method is adaptive , therefore, highly efficient for describing nonlinear and non?stationary signals.
应用推荐