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Anomaly Detection Using Predictive Convolutional Long Short-Term Memory Units

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Figure

Figure 1: A Simple Feed Forward Neural Network. The nodes in the input layer is the input data, while the nodes in the hidden and output layers are perceptrons
Figure 3: A visualization of the LeNet architecture. It combined convolutional, pooling, and fully connected layers to learn a model that can solve classification problems
Figure 5: Long Short-term Memory Cell
Figure 7: The composite structure for unrolled LSTM unit. Blue lines represent potential conditioning
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