Kernel-risk-sensitive conjugate gradient algorithm with Student's-t distribution based random fourier features
Kernel-risk-sensitive loss (KRSL) achieves an efficient performance surface, which has been applied in the kernel adaptive filters (KAFs) successfully. However, the KRSL based KAFs use the stochastic gradient descent (SGD) method in the optimization, which usually suffer from inadequate accuracy wit...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
John Wiley and Sons Inc
2023
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| Subjects: | |
| Online Access: | View Fulltext in Publisher |