{"id":22701,"date":"2015-09-24T19:55:44","date_gmt":"2015-09-24T19:55:44","guid":{"rendered":"http:\/\/ahay.org\/blog\/?p=22701"},"modified":"2015-09-24T19:55:44","modified_gmt":"2015-09-24T19:55:44","slug":"tutorial-on-spitz-method-for-pattern-recognition","status":"publish","type":"post","link":"https:\/\/ahay.org\/blog\/2015\/09\/24\/tutorial-on-spitz-method-for-pattern-recognition\/","title":{"rendered":"Tutorial on Spitz method for pattern recognition"},"content":{"rendered":"<p>The example in <a href=\"\/RSF\/book\/rsf\/tutorials\/spitz.html\">rsf\/tutorials\/spitz<\/a> reproduces the tutorial from Karl Schleicher on the Spitz method for signal and noise separation, <a href=\"http:\/\/conference.scipy.org\/scipy2014\/schedule\/presentation\/1734\/\">presented at the 2014 SciPy conference<\/a>. The implementation is different, with Claerbout&#8217;s T-X helical filters instead of Spitz&#8217;s and Schleicher&#8217;s F-X filters.<\/p>\n<p>For more explanation, see:<\/p>\n<ul>\n<li>Spitz, S., 1999, Pattern recognition, spatial predictability, and subtraction of multiple events: The Leading Edge, 18, 55\u201358.<\/li>\n<li>J. F. Claerbout and S. Fomel, 2000, <a href=\"\/RSF\/book\/sep\/spitz\/paper_html\">Spitz makes a better assumption for the signal PEF<\/a>: Stanford Exploration Project, SEP-103, 211-219.<\/li>\n<\/ul>\n<p><img decoding=\"async\" src=\"\/RSF\/book\/rsf\/tutorials\/spitz\/Fig\/gdata.png\" alt=\"\" title=\"\" \/> <img decoding=\"async\" src=\"\/RSF\/book\/rsf\/tutorials\/spitz\/Fig\/gsignoi.png\" alt=\"\" title=\"\" \/><\/p>\n<p>Madagascar users are encouraged to try improving the results.<\/p>\n<p><iframe loading=\"lazy\" width=\"945\" height=\"532\" src=\"https:\/\/www.youtube.com\/embed\/kFXVOaZZr-E?feature=oembed\" frameborder=\"0\" allowfullscreen><\/iframe><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The example in rsf\/tutorials\/spitz reproduces the tutorial from Karl Schleicher on the Spitz method for signal and noise separation, presented at the 2014 SciPy conference. The implementation is different, with Claerbout&#8217;s T-X helical filters instead of Spitz&#8217;s and Schleicher&#8217;s F-X filters. For more explanation, see: Spitz, S., 1999, Pattern recognition, spatial predictability, and subtraction of [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_import_markdown_pro_load_document_selector":0,"_import_markdown_pro_submit_text_textarea":"","activitypub_content_warning":"","activitypub_content_visibility":"local","activitypub_max_image_attachments":4,"activitypub_interaction_policy_quote":"","footnotes":""},"categories":[7],"tags":[],"class_list":["post-22701","post","type-post","status-publish","format-standard","hentry","category-examples"],"_links":{"self":[{"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/posts\/22701","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/comments?post=22701"}],"version-history":[{"count":3,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/posts\/22701\/revisions"}],"predecessor-version":[{"id":22723,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/posts\/22701\/revisions\/22723"}],"wp:attachment":[{"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/media?parent=22701"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/categories?post=22701"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/tags?post=22701"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}