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Python Efficient Hypothesis Management (PyEHM)\n\n[![PyPI](https://img.shields.io/pypi/v/pyehm?color=blue)](https://pypi.org/project/pyehm)\n[![Documentation Status](https://readthedocs.org/projects/pyehm/badge/?version=latest)](https://pyehm.readthedocs.io/en/latest/?badge=latest)\n[![CircleCI](https://circleci.com/gh/sglvladi/pyehm/tree/main.svg?style=shield)](https://circleci.com/gh/sglvladi/pyehm/tree/main)\n[![License](https://img.shields.io/badge/License-EPL%202.0-red.svg)](https://opensource.org/licenses/EPL-2.0)\n[![DOI](https://zenodo.org/badge/385604939.svg)](https://zenodo.org/badge/latestdoi/385604939)\n\nPyEHM is a Python package that includes open-source implementations of the Efficient Hypothesis Management (EHM) \nAlgorithms described in [1], [2] and **covered by the patent** [3].\n\n\u003e [1] Maskell, S., Briers, M. and Wright, R., 2004, August. Fast mutual exclusion. In Signal and Data Processing of \nSmall Targets 2004 (Vol. 5428, pp. 526-536). International Society for Optics and Photonics\n\u003e \n\u003e [2] Horridge, P. and Maskell, S., 2006, July. Real-time tracking of hundreds of targets with efficient exact JPDAF \nimplementation. In 2006 9th International Conference on Information Fusion (pp. 1-8). IEEE \n\u003e \n\u003e [3] Maskell, S., 2003, July. Signal Processing with Reduced Combinatorial Complexity. Patent Reference:0315349.1\n\n## Documentation\nPlease see the [PyEHM documentation](https://pyehm.readthedocs.io/) for installation instructions, API references and \nusage examples.\n\n## License\nPyEHM is licenced under Eclipse Public License 2.0. See [License](LICENSE) for more details.\n\nThis software is the property of [QinetiQ Limited](https://www.qinetiq.com/en/) and any requests for use of the\nsoftware for commercial use or other use outside of the Eclipse Public Licence should be made to QinetiQ Limited.\n\nThe current QinetiQ contact is Richard Lane (rlane1 [at] qinetiq [dot] com).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsglvladi%2Fpyehm","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsglvladi%2Fpyehm","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsglvladi%2Fpyehm/lists"}