A Novel Unsupervised Neuro-Fuzzy System Applied to Circuit Analysis
Hadi Sadoghi Yazdi · 2007
Abstract: In this paper, for the first time, unsupervised neuro-fuzzy system is presented and is applied in circuit analysis. Usually Neuro-fuzzy systems have a learning phase in which the system is trained with input data. But if the training set is unavailable, conventional procedures encounter serious problem. Due to unsupervised character, no learning data is needed. To investigate the method, linear circuit is analyzed. Results are compared with the exact solution.