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本文在人工神经网络中引入模糊集理论，提出一种模糊自适应BP算法。通过奇偶校验和EEG异常波形检测两个实例，验证了新算法在学习速度与性能上都优于传统的BP算法。
This paper introduces fuzzy set theory in artificial neural network and proposes a fuzzy adaptive BP algorithm. The two examples are tested by parity and EEG anomaly waveforms, which verifies that the new algorithm outperforms the traditional BP algorithm in learning speed and performance.