The adaptive chirp mode decomposition method has a good effect on processing chirp signals. The parameter controls the smoothness of the output signal. Too small an will cause a smooth output signal. The parameter controls the instantaneous frequency (IF). If too small a value is used, the output IF will be very smooth. However, rapidly changing IFs require a relatively large . However, the choice of is artificially set, and there are errors in practical applications. Therefore, it employs the state transition algorithm to adaptively optimize to improve the signal-to-noise ratio (SNR) and resolution of the signal. First, as the species number of the state transition algorithm method is set artificially and has a long running time, this paper proposes a Rastrigin optimization test equation to test the optimization time of different species and determine the number of optimal species; second, the state transition algorithm determined by the number of species is employed to adaptively find the in the adaptive chirp mode decomposition algorithm; finally, the optimized adaptive chirp mode decomposition method is applied to the simulation signal and chirp signal from marine animals to verify the proposed method.

中文翻译：

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优化的自适应线性调频模式分解方法在线性调频信号中的应用

自适应线性调频模式分解方法对线性调频信号具有很好的处理效果。该参数控制输出信号的平滑度。太小将导致平滑的输出信号。该参数控制瞬时频率（IF）。如果使用的值太小，则输出IF将非常平滑。但是，快速变化的IF要求相对较大。但是，选择是人为设定的，在实际应用中存在错误。因此，它采用状态转换算法进行自适应优化，以提高信噪比（SNR）和信号分辨率。首先，由于状态转换算法方法的种类数是人为设置的，并且运行时间较长，提出了Rastrigin优化测试方程，对不同物种的优化时间进行测试，确定最优物种的数量。其次，采用由种数确定的状态转移算法自适应地找到自适应线性调频模式分解算法。最后，将优化的自适应线性调频模式分解方法应用于海洋动物的模拟信号和线性调频信号，以验证该方法的有效性。