{"id":34,"date":"2016-02-26T21:48:59","date_gmt":"2016-02-26T21:48:59","guid":{"rendered":"http:\/\/forell.local\/?page_id=34"},"modified":"2016-02-26T21:48:59","modified_gmt":"2016-02-26T21:48:59","slug":"services","status":"publish","type":"page","link":"https:\/\/www.dreik.se\/index.php\/services\/","title":{"rendered":"Services"},"content":{"rendered":"<p>Here are examples of previous assignments:<\/p>\n<ul>\n<li><strong>C++ development<\/strong><br \/>\nFor performance critical projects, C++ is a good choice. See the <a title=\"c++ programming\" href=\"?page_id=21\">C++ page<\/a> for more information.<\/li>\n<li><strong>Fuzzing<\/strong><br \/>\nNot many code bases survive fuzzing for long. I have successfully used libFuzzer and afl to uncover bugs. I have found (and fixed some) bugs in curl, libfmt, simdjson and tnef.<\/li>\n<li><strong>Programming in Octave and Matlab<\/strong><br \/>\nI use Octave for investigating and prototyping mathematical problems. The prototype can sometimes be used as a reference during implementation in another language such as C++.<\/li>\n<li><strong>Machine learning<\/strong><br \/>\nSome problems can be efficiently solved by applying machine learning techniques. <a title=\"Track condition analyzer\" href=\"?page_id=36\">See the track condition analyzer page<\/a> for an example.<\/li>\n<li><strong>Probability analysis<\/strong><br \/>\nIn many areas, reasoning about uncertainty is important.<\/li>\n<li><strong>Equivalent conicity calculations (railway)<br \/>\n<\/strong>See the <a title=\"Equivalent conicity\" href=\"?page_id=27\">equivalent conicity page<\/a>.<strong><br \/>\n<\/strong><\/li>\n<li><strong>Kalman filtering<\/strong><br \/>\nBeing invented in the 60&#8217;s, the Kalman filter is still one of the most important methods for estimation and signal fusion. It is used to estimate unknown properties based on noisy measurements.<\/li>\n<li><strong>Particle filtering<\/strong><br \/>\nSome estimation problems are not possible to fit in to the model used by the Kalman filter. The particle filter is a general method to solve estimation problems, but is computationally expensive compared to the Kalman filter. Problems where the system evolves according to a nonlinear model and\/or is subject to non-Gaussian noise are preferably approached with a particle filter.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Here are examples of previous assignments: C++ development For performance critical projects, C++ is a good choice. See the C++ page for more information. Fuzzing Not many code bases survive fuzzing for long. I have successfully used libFuzzer and afl to uncover bugs. I have found (and fixed some) bugs in curl, libfmt, simdjson and [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-34","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.dreik.se\/index.php\/wp-json\/wp\/v2\/pages\/34","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.dreik.se\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.dreik.se\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.dreik.se\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.dreik.se\/index.php\/wp-json\/wp\/v2\/comments?post=34"}],"version-history":[{"count":0,"href":"https:\/\/www.dreik.se\/index.php\/wp-json\/wp\/v2\/pages\/34\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.dreik.se\/index.php\/wp-json\/wp\/v2\/media?parent=34"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}