Multilayer perceptron neural networks to compute quasistatic parameters of asymmetric coplanar waveguides

Übeylı, Elif Derya; Güler, İnan

doi:10.1016/j.neucom.2004.04.005

Cited by 45 publications

(13 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These transducers have already been used for precise flow-volume measurements with high accuracy and stability [15] . The acceptability and reproducibility criteria were adopted as per the recommendations given by American Thoracic Society (ATS ) [11,16] . Spirometric data on Vital Capacity (VC), Forced Capacity (FVC), Forced Expiratory Volume in 1st second (FEV1), ratio of FEV1 to FVC (FEV1%), ratio of FEV1 to VC and Peak Expiratory Flow (PEF) were collected.…”

Section: Methodsmentioning

confidence: 99%

“…2, constitute one of the most popular feed forward neural networks [10] . MLPNNs have features such as the ability to learn and generalize, smaller training set requirements, fast operation, ease of implementation and therefore are the most commonly used neural network architectures [8,11] . Contrary to feed forward networks, Recurrent Neural networks (RNs) are models with bi-directional data flow.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Detection of Respiratory Abnormalities Using Artificial Neural Networks

Baemani¹,

Monadjemi²,

Moallem³

2008

J. of Computer Science

View full text Add to dashboard Cite

Problem Statement: Lung disease is a major threat to the human health regarding the industrial life, air pollution, smoking, and infections. Lung function tests are often performed using spirometry. Approach: The present study aims at detecting obstructive and restrictive pulmonary abnormalities. Lung function tests are often performed using spirometry. In this study, the data were obtained from 250 volunteers with standard recording protocol in order to detect and classify pulmonary diseases into normal, obstructive and restrictive. Firstly, spirometric data was statistically analyzed concerning its significance for neural networks. Then, such parameters were presented as input to MLP and recurrent networks. Results: These two networks detected normal and abnormal disorders as well as obstructive and restrictive patterns, respectively. Moreover, the output data was confirmed by measuring accuracy and sensitivity. Conclusion: The results show that the proposed method could be useful for detecting the function of respiratory system.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Detection of Respiratory Abnormalities Using Artificial Neural Networks

Baemani¹,

Monadjemi²,

Moallem³

2008

J. of Computer Science

View full text Add to dashboard Cite

show abstract

“…They conclude that the QP algorithm had a better performance to the application. Finally, authors in [18] compared BP, DBD, extended DBD, QP, and LM algorithms to compute the quasistatic parameters, the characteristic impedance and the effective dielectric constant, of the asymmetric coplanar waveguides (ACPWs). The results of the LM algorithm for the quasistatic parameters of the ACPWs were in very good agreement with the results available in the literature.…”

Section: Learning Algorithmsmentioning

confidence: 99%

Artificial Neural Network Model for the Prediction of Thunderstorms over Kolkata

J¹,

Idicula²,

Francis³

2012

IJCA

View full text Add to dashboard Cite

Severe thunderstorms frequently occur over the eastern and north-eastern states of India during the pre-monsoon season (March-May). Forecasting thunderstorm is one of the most difficult tasks in weather prediction, due to their rather small spatial and temporal extension and the inherent non-linearity of their dynamics and physics. In this paper, experiments are conducted on artificial neural network (ANN) model to predict severe thunderstorms that occurred over Kolkata on 3

show abstract

“…The existing gradient-based techniques, such as back propagation (BP) and Levenberg-Marquardt (LM) algorithm, had been used to train ANNs for constructing the analysis models of various microwave transmission lines [13][14][15]. It is found from [13][14][15] that the LM algorithm can provide a very strong performance as being fast and accurate algorithm. So the LM algorithm will be used to train the proposed analysis model for ACPWs with finite dielectric thickness and ground-plane width.…”

Section: Ann-based Analysis Modelmentioning

confidence: 99%

An ANN-based analysis model for ACPWs with finite dimensions

Wang

Fang

2012

2012 IEEE MTT-S International Microwave Workshop Series on Millimeter Wave Wireless Technology and Applications

View full text Add to dashboard Cite

An analysis model based on artificial neural networks (ANNs) is proposed for computing the effective permittivities and characteristic impedances of asymmetric coplanar waveguides (ACPWs) with finite dielectric thickness and ground-plane width. First, the ACPWs are analyzed with the conformal mapping technique (CMT) to obtain the training data sets. Then, the Levenberg-Marquardt (LM) algorithm is used to train the ANNs for obtaining an accurate analysis model. The models also can be used for symmetric coplanar waveguides. At last, the models are validated by the comparison with the CMT analysis and measured results.

show abstract

Multilayer perceptron neural networks to compute quasistatic parameters of asymmetric coplanar waveguides

Cited by 45 publications

References 38 publications

Detection of Respiratory Abnormalities Using Artificial Neural Networks

Detection of Respiratory Abnormalities Using Artificial Neural Networks

Artificial Neural Network Model for the Prediction of Thunderstorms over Kolkata

An ANN-based analysis model for ACPWs with finite dimensions

Contact Info

Product

Resources

About