کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
9699175 | 1461440 | 2005 | 5 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Accurate modeling of low-cost SiGe:C-HBTs using adaptive neuro-fuzzy inference system
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی برق و الکترونیک
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
A low-cost BiCMOS SiGe:C-HBT is accurately modeled using adaptive neuro-fuzzy inference system (ANFIS) for the first time. The Volterra kernel-based approach can be suitable for this new kind of modeling. The model has been trained and tested with different sets of input/output data. Accuracy of the model is checked for all the DC and S parameters in a wide range of bias and frequencies. On the validation of the ANFIS model, the average error is found to be less than 4%. Especially in high-current and high-frequency regions, the ANFIS model is proved to be excellent unlike most of the physics-based equivalent circuit models that fail to track the actual device behavior.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Materials Science in Semiconductor Processing - Volume 8, Issues 1â3, FebruaryâJune 2005, Pages 307-311
Journal: Materials Science in Semiconductor Processing - Volume 8, Issues 1â3, FebruaryâJune 2005, Pages 307-311
نویسندگان
A. Chakravorty, R.F. Scholz, B. Senapati, D. Knoll, A. Fox, R. Garg, C.K. Maiti,