Results 1 
5 of
5
Hybrid genetic algorithm for electromagnetic topology optimization
 IEEE Trans. Magn
, 2003
"... Abstract—This paper proposes a hybrid genetic algorithm (GA) for electromagnetic topology optimization. A twodimensional (2D) encoding technique, which considers the geometrical topology, is first applied to electromagnetics. Then, a 2D geographic crossover is used as the crossover operator. A ..."
Abstract

Cited by 5 (1 self)
 Add to MetaCart
(Show Context)
Abstract—This paper proposes a hybrid genetic algorithm (GA) for electromagnetic topology optimization. A twodimensional (2D) encoding technique, which considers the geometrical topology, is first applied to electromagnetics. Then, a 2D geographic crossover is used as the crossover operator. A novel local optimization algorithm, called the on/off sensitivity method, hybridized with the 2D encoded GA, improves the convergence characteristics. The algorithm was verified by applying it to various case studies, and the results are presented herein. Index Terms—Genetic algorithm (GA), geographic crossover, local optimization, topology optimization, twodimensional (2D) encoding. I.
Estimating parametric linesource models with electroencephalography
 IEEE Trans. Biomed. Eng
, 2006
"... Abstract—We develop three parametric models for electroencephalography (EEG) to estimate current sources that are spatially distributed on a line. We assume a realistic head model and solve the EEG forward problem using the boundary element method (BEM). We present the models with increasing degree ..."
Abstract

Cited by 1 (1 self)
 Add to MetaCart
(Show Context)
Abstract—We develop three parametric models for electroencephalography (EEG) to estimate current sources that are spatially distributed on a line. We assume a realistic head model and solve the EEG forward problem using the boundary element method (BEM). We present the models with increasing degrees of freedom, provide the forward solutions, and derive the maximumlikelihood estimates as well as CramérRao bounds of the unknown source parameters. A series of experiments are conducted to evaluate the applicability of the proposed models. We use numerical examples to demonstrate the usefulness of our linesource models in estimating extended sources. We also apply our models to the real EEG data of N20 response that is known to have an extended source. We observe that the linesource models explain the N20 measurements better than the dipole model. Index Terms—CramérRao bounds, EEG, extended source modeling.
BioMed Central Review Review on solving the inverse problem in EEG source analysis
, 2008
"... This is an Open Access article distributed under the terms of the Creative Commons Attribution License ..."
Abstract
 Add to MetaCart
(Show Context)
This is an Open Access article distributed under the terms of the Creative Commons Attribution License
15. SUBJECT TERMS
"... a. REPORT 16. SECURITY CLASSIFICATION OF: Decades of heavy investment in laboratorybased brain imaging and neuroscience have led to foundational insights into how humans sense, perceive, and interact with the external world. However, it is argued that fundamental differences between laboratorybase ..."
Abstract
 Add to MetaCart
(Show Context)
a. REPORT 16. SECURITY CLASSIFICATION OF: Decades of heavy investment in laboratorybased brain imaging and neuroscience have led to foundational insights into how humans sense, perceive, and interact with the external world. However, it is argued that fundamental differences between laboratorybased and naturalistic human behavior may exist. Thus, it remains unclear how well the current knowledge of human brain function translates into the highly dynamic real world. While some demonstrated successes in realworld neurotechnologies are observed, particularly in the area of braincomputer interaction technologies, innovations and developments to date are limited to a small science and technology