{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T13:14:51Z","timestamp":1753881291252,"version":"3.41.2"},"reference-count":24,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2012,3,14]],"date-time":"2012-03-14T00:00:00Z","timestamp":1331683200000},"content-version":"vor","delay-in-days":73,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"funder":[{"name":"Ministry for Health, Welfare and Family Affairs, Republic of Korea","award":["A090794"],"award-info":[{"award-number":["A090794"]}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Applied Mathematics"],"published-print":{"date-parts":[[2012,1]]},"abstract":"<jats:p>For solving electroencephalographic forward problem, coupled method of finite element method (FEM) and fast moving least square reproducing kernel method (FMLSRKM) which is a kind of meshfree method is proposed. Current source modeling for FEM is complicated, so source region is analyzed using meshfree method. First order of shape function is used for FEM and second order for FMLSRKM because FMLSRKM adopts point collocation scheme. Suggested method is tested using simple equation using 1\u2010, 2\u2010, and 3\u2010dimensional models, and error tendency according to node distance is studied. In addition, electroencephalographic forward problem is solved using spherical head model. Proposed hybrid method can produce well\u2010approximated solution.<\/jats:p>","DOI":"10.1155\/2012\/840593","type":"journal-article","created":{"date-parts":[[2012,3,14]],"date-time":"2012-03-14T21:03:11Z","timestamp":1331758991000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Coupling of Point Collocation Meshfree Method and FEM for EEG Forward Solver"],"prefix":"10.1155","volume":"2012","author":[{"given":"Chany","family":"Lee","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jong-Ho","family":"Choi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ki-Young","family":"Jung","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hyun-Kyo","family":"Jung","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2012,3,14]]},"reference":[{"key":"e_1_2_8_1_2","doi-asserted-by":"publisher","DOI":"10.1186\/1743-0003-4-46"},{"key":"e_1_2_8_2_2","doi-asserted-by":"publisher","DOI":"10.1162\/jocn.1993.5.2.162"},{"key":"e_1_2_8_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/79.962275"},{"key":"e_1_2_8_4_2","article-title":"Principles of cognitive neuroscience","volume":"83","author":"Purves D.","year":"2008","journal-title":"Sinauer Associates"},{"key":"e_1_2_8_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMAG.2006.892286"},{"key":"e_1_2_8_6_2","doi-asserted-by":"publisher","DOI":"10.1088\/0031-9155\/40\/3\/001"},{"key":"e_1_2_8_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/10.748978"},{"key":"e_1_2_8_8_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMAG.2005.846286"},{"key":"e_1_2_8_9_2","doi-asserted-by":"publisher","DOI":"10.1109\/10.605431"},{"key":"e_1_2_8_10_2","first-page":"35","article-title":"A posteriori error estimation and adaptive node refinement for fast moving least square reproducing kernel (FMLSRK) method","volume":"20","author":"Lee C.","year":"2007","journal-title":"Computer Modeling in Engineering & Sciences"},{"key":"e_1_2_8_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/0013-7944(94)00153-9"},{"key":"e_1_2_8_12_2","doi-asserted-by":"publisher","DOI":"10.1002\/nme.2670"},{"volume-title":"Meshfree Methods for Partial Differential Equations II","year":"2003","author":"Barth T. 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