ARTÍCULO
TITULO

Gaussian Mixture Density based Analytical Model of Noise Induced Variation in Key Parameter of Electronically Tunable Device

Rawid Banchuin    

Resumen

In this research, the Gaussian mixture density based analytical model of variation in key parameter of electronically tunable device has been originally proposed. The proposed model is applicable to any electronically tunable device with its tuning variable has been affected by any kind of noise with arbitrary parameters. It has been found from the verification by using different electronically tunable device based empirical distributions and the Kolmogorov-Smirnov tests that this novel model is very accurate. So, it has been found to be a convenient mathematical tool for the analysis and design of various electronically tunable device based circuits.

 Artículos similares

       
 
Luca Scrucca    
Imbalanced data present a pervasive challenge in many real-world applications of statistical and machine learning, where the instances of one class significantly outnumber those of the other. This paper examines the impact of class imbalance on the perfo... ver más
Revista: Algorithms

 
Feihu Zhang, Diandian Xu and Chensheng Cheng    
Multi-vehicle collaborative mapping proves more efficient in constructing maps in unfamiliar underwater environments in comparison to single-vehicle methods. One of the pivotal hurdles of Simultaneous Localization and Mapping (SLAM) with multiple underwa... ver más

 
Saharsh Barve, Jody M. Webster and Rohitash Chandra    
Environmental damage has been of much concern, particularly in coastal areas and the oceans, given climate change and the drastic effects of pollution and extreme climate events. Our present-day analytical capabilities, along with advancements in informa... ver más
Revista: Information

 
James Simon Flynn, Cinzia Giannetti and Hessel Van Dijk    
In many manufacturing systems, anomaly detection is critical to identifying process errors and ensuring product quality. This paper proposes three semi-supervised solutions to detect anomalies in Direct Current (DC) Nut Runner engine assembly processes. ... ver más
Revista: AI

 
Qingji Guan, Qinrun Chen and Yaping Huang    
Chest X-ray image classification suffers from the high inter-similarity in appearance that is vulnerable to noisy labels. The data-dependent and heteroscedastic characteristic label noise make chest X-ray image classification more challenging. To address... ver más
Revista: Algorithms