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{ "category": "SciPy 2013", "language": "English", "slug": "scikit-fuzzy-a-new-scipy-toolkit-for-fuzzy-logic", "speakers": [], "tags": [ "Tech" ], "id": 2019, "state": 1, "title": "Scikit-Fuzzy: A New SciPy Toolkit for Fuzzy Logic; SciPy 2013 Presentation", "summary": "Authors: Warner, Joshua, Mayo Clinic Department of Biomedical Engineering; Ottesen, Hal H., Adjunct Professor\n\nTrack: General\n\nScikit-fuzzy is a robust set of foundational tools for problems involving fuzzy logic and fuzzy systems. This area has been a challenge for the scientific Python community, largely because the common first exposure to this topic is through the MATLAB\u00ae Fuzzy Logic Toolbox\u2122. This talk officially introduces a general set of original fuzzy logic algorithms to the scientific Python community which predate the commercial toolbox, were released under the 3-clause BSD license, and were translated to Python by an author who never used the MathWorks\u00c2\u00ae Fuzzy Logic Toolbox\u2122.\n\nThe current capabilities of scikit-fuzzy include: fuzzy membership function generation; fuzzy set operations; lambda-cuts; fuzzy mathematics including Zadeh's extension principle, the vertex method, and the DSW method; fuzzy implication given an IF THEN system of fuzzy rules (via Mamdani [min] or Larsen [product] implication); various defuzzification algorithms; fuzzy c-means clustering; and Fuzzy Inference Ruled by Else-action (FIRE) denoising of 1d or 2d signals.\n\nThe goals of scikit-fuzzy are to provide the community with a robust toolkit of independently developed and implemented fuzzy logic algorithms, filling a void in the capabilities of scientific and numerical Python, and to increase the attractiveness of scientific Python as a valid alternative to closed-source options. Scikit-fuzzy is structured similarly to scikit-learn and scikit-image, current source code is available on GitHub, and pull requests are welcome.", "description": "", "quality_notes": "", "copyright_text": "http://www.youtube.com/t/terms", "embed": "<object width=\"640\" height=\"390\"><param name=\"movie\" value=\"http://youtube.com/v/qUQf1JxnTnY?version=3&amp;hl=en_US\"></param><param name=\"allowFullScreen\" value=\"true\"></param><param name=\"allowscriptaccess\" value=\"always\"></param><embed src=\"http://youtube.com/v/qUQf1JxnTnY?version=3&amp;hl=en_US\" type=\"application/x-shockwave-flash\" width=\"640\" height=\"390\" allowscriptaccess=\"always\" allowfullscreen=\"true\"></embed></object>", "thumbnail_url": "http://i1.ytimg.com/vi/qUQf1JxnTnY/hqdefault.jpg", "duration": null, "video_ogv_length": null, "video_ogv_url": null, "video_ogv_download_only": false, "video_mp4_length": null, "video_mp4_url": null, "video_mp4_download_only": false, "video_webm_length": null, "video_webm_url": null, "video_webm_download_only": false, "video_flv_length": null, "video_flv_url": null, "video_flv_download_only": false, "source_url": "http://www.youtube.com/watch?v=qUQf1JxnTnY", "whiteboard": "needs editing", "recorded": "2013-07-02", "added": "2013-07-04T10:08:39", "updated": "2014-04-08T20:28:26.365" }