Abstract: Highlights•We propose a threshold value filter pooling method.•The pooling is capable of avoiding the accumulation of noise in histogram-pooling.•We propose a Matthew effect normalization method to highlight the useful information.•We apply such two methods in a dimensionality reduction framework.•The framework can reduce dimensionality and increase classification accuracy.
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