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README.md
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@@ -36,6 +36,8 @@ The data frame has two columns consisting of "Timestamp" and "DcDiffAvg".
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Every cycle is done, the average time interval to the next DC clock for each cycle is cacluated in ns, and this value shows a peculiar sawtooth pattern as follows.
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Using this dataset **the autoencoder model** can be trained *to detect anomalies in case of unstable communication between the master(Main device) and sub-devices*.
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### Dataset Description
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Every cycle is done, the average time interval to the next DC clock for each cycle is cacluated in ns, and this value shows a peculiar sawtooth pattern as follows.
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Using this dataset **the autoencoder model** can be trained *to detect anomalies in case of unstable communication between the master(Main device) and sub-devices*.
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For detail information and source code, find the following link.
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https://github.com/kyoungje/WMXAnomalyDetection/tree/main
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### Dataset Description
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