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
- Nitika, Kuldeep Chaudhary, A critical review of social media advertising literature: Visualization and bibliometric approach , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Selva Kumar D, Revisiting the challenges of disinvestment practices and central public sector enterprises (CPSEs): Indian empirical evidence , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- Rashmi Chandra, Afroz Alam, Phytochemical Analysis Using X-ray Diffraction Spectroscopy (XRD) and GC-MS Analysis of Bioactive Compounds in Cucumis sativus L. (Angiosperms; Cucurbitaceae) , The Scientific Temper: Vol. 13 No. 01 (2022): The Scientific Temper
- Karan Berry, Shiv Kumar, Exploring the mediating role of gastronomic experience in tourist satisfaction: A multigroup analysis , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Annalakshmi D, C. Jayanthi, A secured routing algorithm for cluster-based networks, integrating trust-aware authentication mechanisms for energy-efficient and efficient data delivery , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- V. Parimala, D. Ganeshkumar, Solar energy-driven water distillation with nanoparticle integration for enhanced efficiency, sustainability, and potable water production in arid regions , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Arvind K Shukla, Balaji V, Dharani R, M Ananthi, R Padmavathy, Romala V. Srinivas, Precision agriculture predictive modeling and sensor analysis for enhanced crop monitoring , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- Adedotun Adedayo F, Odusanya Oluwaseun A, Adesina Olumide S, Adeyiga J. A, Okagbue, Hilary I, Oyewole O, Prediction of automobile insurance fraud claims using machine learning , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Muhammed Jouhar K. K., Dr. K. Aravinthan, An improved social media behavioral analysis using deep learning techniques , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- P. Pattunnarajam, Janani G, A. Vijayaraj, Sathiya Priya S, Enhanced routing strategy of wireless sensor network based on fifth generation communication technology , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
<< < 5 6 7 8 9 10 11 12 13 14 > >>
You may also start an advanced similarity search for this article.