The multi-kernel maximum mean discrepancy (MK-MMD), which is the most efficient of existing adaptive approaches, is implemented in the fully connected layer of the original model's feature extraction network. Finally, through the process of fine-tuning, the model that ...
To this end, a Kernel Adaptive Filter (KAF) algorithm extracts the dynamic of each channel, relying on the similarity between multiple realizations through the Maximum Mean Discrepancy (MMD) criterion. To assemble dynamics extracted from all MoCap data, center kernel alignment (CKA) is used to ...
Therefore, it verifies that the MKJDA can construct a more effective and robust representation for cross-domain classification tasks of the bearing fault diagnosis because the dynamic distribution alignment and multi-kernel MMD are introduced into the TL method. Similarly, the statistical filter also ...
Combined with the multi-source domain adaptive method, the public feature extraction module is used to initially achieve feature mining of the image; the MK-MMD algorithm of the domain-specific adaptive module reduces the difference in feature distribution between the source an...
Finally, the maximum mean difference (MMD) is introduced, as a measure to characterize the disparity between the projects, and an adversarial loss function is utilized to minimize the distance between these feature representations. Wang et al. [22] presented a few-shot learning-based balanced ...
This leading order approximation shows that the MMD depends intricately on the fast﹕low systems parameters, which can influence the detection of potential early﹚arning signs before critical transitions. However, the MMD turns out to be an excellent binary classifier to detect the change﹑oint ...
In particular, we show that a formal approximation of the MMD near fast subsystem bifurcation points can be computed to leading order. This leading order approximation shows that the MMD depends intricately on the fast-slow systems parameters, which can influence the detection of potential early-...