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Additionally, GDBP MLP compared here is based on derivative computations which impose high complexity, while the proposed method is derivative free.
It is obvious that SNP is more accurate than MLP with GDBP algorithm in some datasets.
Secondly, in classification problems, the performance of supervised excitatory and inhibitory learning algorithm is higher than gradient descent backpropagation (GDBP).