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Different types of kernels can be used to train SVMs.
Three types of kernels are used, shown in the left panels of Fig. 1.
Then results using the other types of kernels and stimuli are briefly illustrated and summarized.
For SVM, different types of kernels such as linear, RBF, polynomial, sigmoid, and histogram intersection (HI) can be used.
Here we use post-spike currents generated via three types of kernels [23, 24]: bursting, decaying, and delaying kernel, all modeled by the difference between two decaying exponentials, but any kernel could be used.
Other types of kernels could have been used; however, since the Gaussian kernel is commonly used for the kernel PCA, the SVDD, and the Parzen density, this kernel is the only kernel used with respect to the experiments reported here.
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Some types of kernel, however, can be computed using matrix multiplication.
While for equation (1.1), only few special types of kernel functions are known.
Therefore, in this article, we introduce two types of kernel functions.
In the proposed method, we newly defined two types of kernel functions.
The proposed method constructs two types of kernel functions for human motions and music pieces, respectively.
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