Analog Circuits Based Fault Diagnosis using ANN and SVM
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2023.14.2.19Keywords:
Artificial Neural Networks, Kernel Principal Component Analysis, Support Vector Machine.Dimensions Badge
Issue
Section
License
Copyright (c) 2023 The Scientific Temper
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
In this study, we provide a technique for identifying analog errors using a neural network and an SVM (SVM). The study's major objective is to produce a trustworthy diagnostic based on a technique that reduces testing durations by resolving the problem of component tolerances.The suggested strategy uses an artificial neural network and a backward propagation mechanism. The impact of methods like Principal Component Analysis on feature extraction is discussed in this work. The simulation results show that the technique is effective and efficient for fault identification in tolerant mixed-signal circuits.Abstract
How to Cite
Downloads
Similar Articles
- Rita Ganguly, Dharmpal Singh, Rajesh Bose, The next frontier of explainable artificial intelligence (XAI) in healthcare services: A study on PIMA diabetes dataset , The Scientific Temper: Vol. 16 No. 05 (2025): The Scientific Temper
- Brijesh Singh, Ajay Massand, Determinants of Gen Z’s adoption of chatbots in online shopping: An empirical investigation , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- Hardik Talsania, Kirit Modi, Attention-Enhanced Multi-Modal Machine Learning for Cardiovascular Disease Diagnosis , The Scientific Temper: Vol. 17 No. 01 (2026): The Scientific Temper
- Ankush Wadhwa, Sanjay Nandal, Development of an Index in Social Science: A Systematic Literature Review , The Scientific Temper: Vol. 16 No. 03 (2025): The Scientific Temper
- B. S. E. Zoraida, J. Jasmine Christina Magdalene, Smart grid precision: Evaluating machine learning models for forecasting of energy consumption from a smart grid , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- C. Premila Rosy, Clustering of cancer text documents in the medical field using machine learning heuristics , The Scientific Temper: Vol. 16 No. 05 (2025): The Scientific Temper
- A. Kamatchi, V. Maniraj, An accurate Prediction and Classification of early Alzheimer’s Diseases using Machine Learning Algorithm , The Scientific Temper: Vol. 17 No. 03 (2026): The Scientific Temper
- S ChandraPrabha, S. Kantha Lakshmi, P. Sivaraaj, Data analysis and machine learning-based modeling for real-time production , The Scientific Temper: Vol. 14 No. 02 (2023): The Scientific Temper
- Prabu Gopal, M. Jeyaseelan, Familial support of rural elderly in indian family system: A sociological analysis , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Temesgen Asfaw, Customer churn prediction using machine-learning techniques in the case of commercial bank of Ethiopia , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
<< < 2 3 4 5 6 7 8 9 10 11 > >>
You may also start an advanced similarity search for this article.
