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Collection of the time-series data which utilizes the self regression model and treatment manner

机译:利用自我回归模型和处理方式收集时间序列数据

摘要

To constitute a filter adapted to such object part as an unknown sound for such time-series data as sound and vibration. SOLUTION: When processing such time-series data as collected sound and vibration through filters 3 which are constituted by an autoregressive model and a plurality of filters 3 are provided so that each autoregressive coefficient can be set and a POWER spectrum is calculated according to an autoregressive model for a desired part including a significant signal among the collected time-series data. When a calculated POWER spectrum differs from that calculated in the past and an autoregressive coefficient is calculated 4, the coefficient is set to a non-set filter, and at the same time and information ON the POWER spectrum is stored and is compared with POWER spectrum which is calculated later. Since a filter is constituted from the collected time-series data and a corresponding filter can be constituted also for an unknown desired art to identify succeeding same desired part.
机译:为诸如声音和振动之类的时间序列数据构成适合于诸如未知声音之类的物体部分的滤波器。解决方案:当通过由自回归模型构成的滤波器3处理诸如收集的声音和振动之类的时间序列数据时,提供了多个滤波器3,以便可以设置每个自回归系数,并根据自回归计算POWER频谱收集的时间序列数据中包含重要信号的所需部分的模型。当计算出的POWER谱不同于过去计算出的POWER谱并计算出自回归系数4时,将该系数设置为未设置的滤波器,并同时存储有关POWER谱的信息并将其与POWER谱进行比较稍后计算。由于由收集的时间序列数据构成滤波器,并且还可以为未知的期望技术构成相应的滤波器,以识别后续的相同期望部分。

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