TY - JOUR N2 - The paper presents Gupta's relational decomposition technique expanded on linguistic level. It allows to reduce the hardware cost of the fuzzy system or the computing time of the final result, especially when referring to First Aggregation Then Inference (FATI) relational systems or First Inference Then Aggregation (FITA) rule systems. The inference result of the hierarchical system using decomposition technique is more fuzzy than of the classical system. The paper describes a linguistic decomposition technique based on partitioning the knowledge base of the fuzzy inference system. It allows to decrease or even totally remove a redundant fuzziness of the inference result. L1 - http://www.czasopisma.pan.pl/Content/110729/PDF-MASTER/(56-1)71.pdf L2 - http://www.czasopisma.pan.pl/Content/110729 PY - 2008 IS - No 1 EP - 76 KW - membership function KW - fuzzy rule KW - fuzzy relation KW - knowledge base KW - relational decomposition KW - linguistic decomposition KW - First Inference Then Aggregation system (FITA) KW - First Aggregation Then Inference system (FATI) KW - fuzzy inference A1 - Wyrwoł, B. VL - vol. 56 DA - 2008 T1 - Linguistic decomposition technique based on partitioning the knowledge base of the fuzzy inference system SP - 71 UR - http://www.czasopisma.pan.pl/dlibra/publication/edition/110729 T2 - Bulletin of the Polish Academy of Sciences Technical Sciences ER -