Application of Quantum-Clustering on Thermograms of WiFi Circuits in Different Operation Modes
| Autor: | M. Hesham Farouk, Nihal Yassin |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Computer science
business.industry Noise (signal processing) Initialization Pattern recognition 02 engineering and technology 01 natural sciences Computer Graphics and Computer-Aided Design 010309 optics Robustness (computer science) 0103 physical sciences Pattern recognition (psychology) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Artificial intelligence business Cluster analysis Randomness Electronic circuit Quantum clustering |
| Zdroj: | Pattern Recognition and Image Analysis. 29:565-571 |
| ISSN: | 1555-6212 1054-6618 |
| DOI: | 10.1134/s1054661819030179 |
| Popis: | The purpose of this work is to evaluate the efficacy of applying a model-based quantum clustering (QC) algorithm on thermograms of functional modes in WiFi circuits. As unsupervised clustering algorithm, it can work on clusters of any shape and does not require any prior information. QC proves its efficacy for many applications, it has been tested, in this work, and compared with other algorithms which suffer randomness according to initialization. The tests are conducted on thermograms of an electronic chip in different operation modes. The benefits of QC are confirmed through performance analysis of clustering algorithms. Robustness analysis is also conducted against white-Gaussian noise clustering and so on classification of actual WiFi circuit operation modes based on thermograms. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full text from SpringerLink