Fuzzy data processing using polynomial bidirectional hetero-associative network

Abstract This investigation presents a novel method of fuzzy data processing using polynomial bidirectional hetero-associative network (PBHAN). This has a higher capacity for pattern pair storage than that of the conventional bidirectional associative memories (BAMs) and fuzzy memories. In addition, a new energy function is defined. The PBHAN takes advantage of fuzzy characteristics in evolution equations such that the signal-noise-ratio (SNR) is significantly increased. The energy of the PBHAN defined by the proposed energy function decreases as the recall process proceeds, thereby ensuring the stability of the system. In this work, we prove the stability of fuzzy data processing using PBHAN. The increase of SNR consequently enhances the capacity of the PBHAN. The capacity of the fuzzy data processing using PBHAN in the worst case is also estimated.

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