论文标题
使用自相关的删除率估计连续和离散信号的随机性
Estimation of the Randomness of Continuous and Discrete Signals Using the Disentropy of the Autocorrelation
论文作者
论文摘要
通过物理或非物理过程产生的信号中的随机性可以揭示有关该过程的重要信息。例如，心电图信号中随机性的存在可能表明心脏病。在手上，语音信号中缺乏随机性可能表明说话者是一台机器。因此，在许多不同领域中，量化信号中的随机性是一项重要任务。在这个方向上，目前的工作建议将自相关函数的分离作为衡量随机性的度量。显示了使用嘈杂和混乱信号的示例。
The amount of randomness in a signal generated by physical or non-physical process can reveal important information about that process. For example, the presence of randomness in ECG signals may indicate a cardiac disease. On the hand, the lack of randomness in a speech signal may indicate the speaker is a machine. Hence, to quantify the amount of randomness in a signal is an important task in many different areas. In this direction, the present work proposes to use the disentropy of the autocorrelation function as a measure of randomness. Examples using noisy and chaotic signals are shown.
