✦ LIBER ✦

A combination of FDTD and least-squares support vector machines for analysis of microwave integrated circuits

✍ Scribed by Y. Yang; S. M. Hu; R. S. Chen

Publisher: John Wiley and Sons
Year: 2004
Tongue: English
Weight: 127 KB
Volume: 44
Category: Article
ISSN: 0895-2477
DOI: 10.1002/mop.20615

No coin nor oath required. For personal study only.

✦ Synopsis

Abstract

This paper presents a new combination of the finite‐difference time‐domain (FDTD) method and the least‐squares support vector machines (LS‐SVM) technique. The LS‐SVM is a statistical‐learning method which has a self‐contained basis of statistical‐learning theory and excellent learning performance. A short segment of an FDTD record is used to train the LS‐SVM predictor in order to obtain an accurate future realization. Numerical simulations for two typical microwave filters demonstrate that the LS‐SVM method can achieve good forecasting accuracy and the efficiency of the FDTD method can be improved by up to 70%. © 2005 Wiley Periodicals, Inc. Microwave Opt Technol Lett 44: 296–299, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.20615

📜 SIMILAR VOLUMES

Combination of particle-swarm optimizati

Combination of particle-swarm optimization with least-squares support vector machine for FDTD time series forecasting

✍ Y. Yang; R. S. Chen; Z. B. Ye 📂 Article 📅 2005 🏛 John Wiley and Sons 🌐 English ⚖ 148 KB

This new circuit (Fig. 8) shows simulated losses of only 15%, which is 30% less than that of Fig. 4. ## CONCLUSION This study has shown that the coupling between two parallel microstrip lines is enhanced by the use of a slot split-ring resonators (SSRRs) defected ground plane. Since the gap betwe

Optimizing the tuning parameters of leas

Optimizing the tuning parameters of least squares support vector machines regression for NIR spectra

✍ T. Coen; W. Saeys; H. Ramon; J. De Baerdemaeker 📂 Article 📅 2006 🏛 John Wiley and Sons 🌐 English ⚖ 323 KB

## Abstract Partial least squares (PLS) is one of the most used tools in chemometrics. Other data analysis techniques such as artificial neural networks and least squares support vector machines (LS‐SVMs) have however made their entry in the field of chemometrics. These techniques can also model no

A coupled FDTD-artificial neural network

A coupled FDTD-artificial neural network technique for large-signal analysis of microwave circuits

✍ S. Goasguen; S. M. El-Ghazaly 📂 Article 📅 2001 🏛 John Wiley and Sons 🌐 English ⚖ 302 KB

We propose a first-order global modeling approach of Monolithic Microwave Integrated Circuits (MMIC) by modeling the active device with a neural network based on a full hydrodynamic model. This neural network describes the nonlinearities of the equivalent circuit parameters of an MESFET implemented

Prediction of municipal solid waste gene

Prediction of municipal solid waste generation with combination of support vector machine and principal component analysis: A case study of Mashhad

✍ R. Noori; M.A. Abdoli; A. Ameri Ghasrodashti; M. Jalili Ghazizade 📂 Article 📅 2009 🏛 American Institute of Chemical Engineers 🌐 English ⚖ 379 KB

Combination of kernel PCA and linear sup

Combination of kernel PCA and linear support vector machine for modeling a nonlinear relationship between bioactivity and molecular descriptors

✍ Guang-Hui Fu; Dong-Sheng Cao; Qing-Song Xu; Hong-Dong Li; Yi-Zeng Liang 📂 Article 📅 2011 🏛 John Wiley and Sons 🌐 English ⚖ 254 KB 👁 1 views

Combination of support vector machines (

Combination of support vector machines (SVM) and near-infrared (NIR) imaging spectroscopy for the detection of meat and bone meal (MBM) in compound feeds

✍ J. A. Fernández Pierna; V. Baeten; A. Michotte Renier; R. P. Cogdill; P. Dardenn 📂 Article 📅 2004 🏛 John Wiley and Sons 🌐 English ⚖ 378 KB 👁 2 views