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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 two-dimen-sional (2-D) encoding technique, which considers the geometrical topology, is first applied to electromagnetics. Then, a 2-D ge-ographic crossover is used as the crossover operator. A ..."
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Abstract—This paper proposes a hybrid genetic algorithm (GA) for electromagnetic topology optimization. A two-dimen-sional (2-D) encoding technique, which considers the geometrical topology, is first applied to electromagnetics. Then, a 2-D ge-ographic crossover is used as the crossover operator. A novel local optimization algorithm, called the on/off sensitivity method, hybridized with the 2-D 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, two-dimensional (2-D) encoding. I.
Estimating parametric line-source models with electroencephalography
- IEEE Trans. Biomed. Eng
, 2006
"... Abstract—We develop three parametric models for electroen-cephalography (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 ..."
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Abstract—We develop three parametric models for electroen-cephalography (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 maximum-likelihood estimates as well as Cramér-Rao bounds of the unknown source pa-rameters. A series of experiments are conducted to evaluate the ap-plicability of the proposed models. We use numerical examples to demonstrate the usefulness of our line-source 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 ob-serve that the line-source models explain the N20 measurements better than the dipole model. Index Terms—Cramér-Rao 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 ..."
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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 laboratory-based 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 laboratory-base ..."
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a. REPORT 16. SECURITY CLASSIFICATION OF: Decades of heavy investment in laboratory-based 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 laboratory-based 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 real-world neurotechnologies are observed, particularly in the area of brain-computer interaction technologies, innovations and developments to date are limited to a small science and technology
