Experimental Study of Low-Power CMOS Amplifiers

1. Introduction

Environmental pressures and resource constraints have brought low-power CMOS amplifiers to the forefront of research on manufacturing processes. Field surveys of manufacturing processes provided the dataset to which adaptive neuro-fuzzy inference was subsequently applied. The proposed algorithm converged reliably within 9 iterations for every case that was tested. The results support the adoption of the proposed method in routine engineering practice.

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2. Materials and Methods

The method is described in the printed article, of which the PDF galley is a faithful rendition.

3. Results and Discussion

Results are reported in full in the PDF, together with the figures and tables referenced above.

4. Conclusion

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