PENGUATAN PENDIDIKAN KARAKTER PEDULI SESAMA MELALUI KEGIATAN EKSTRAKURIKULER RELAWAN




Accelerate Convergence of Polarized Random Fourier Feature-Based Kernel Adaptive Filtering With Variable Forgetting Factor and Step Size

The Lazy Susan random Fourier feature as an efficient kernel approximation method can effectively suppress the network growth of the traditional kernel-based adaptive filtering algorithm.Polarized random Fourier feature kernel least-mean-square(PRFFKLMS) remarkably improved the accuracy performance of random Fourier feature-based kernel least-mean-

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