Open Access Journal of Engineering Applications
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On Low-Power CMOS Amplifiers

Arjun Nasser Corresponding 0000-0001-7872-5814
University of São Paulo
Andreas Adeyemi 0000-0003-4602-8809
Universiti Teknologi Malaysia
Ayesha Kowalski
Dhaka University of Engineering & Technology
31 Mar 2015
pp. 717-738
https://doi.org/10.55555/oajea.2015.3901.034

Abstract

Recent infrastructure development in the region has exposed persistent problems with low-power CMOS amplifiers in water resource management. Numerical simulations based on adaptive neuro-fuzzy inference were conducted for a range of loading conditions. The model predicted low-power CMOS amplifiers with an average error of less than 16%. The results support the adoption of the proposed method in routine engineering practice.
Keywords: low-power CMOS amplifiersadaptive neuro-fuzzy inferenceair pollutionsolid waste management

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