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NQLib](https://github.com/knttnk/NQLib/actions/workflows/test-python-package.yml/badge.svg)](https://github.com/knttnk/NQLib/actions/workflows/test-python-package.yml)\r\n[![PyPI Downloads](https://static.pepy.tech/personalized-badge/nqlib?period=total\u0026units=INTERNATIONAL_SYSTEM\u0026left_color=GRAY\u0026right_color=BLUE\u0026left_text=PyPI+downloads)](https://pepy.tech/projects/nqlib)\r\n[![Anaconda-Server Badge](https://anaconda.org/conda-forge/nqlib/badges/downloads.svg)](https://anaconda.org/conda-forge/nqlib)\r\n\r\nNQLib is a \u003ca href=\"https://www.python.org/\" target=\"_blank\"\u003ePython\u003c/a\u003e library to design noise shaping quantizer for discrete-valued input control.\r\n\r\n## What can I do with NQLib?\r\n\r\nIn the real world, a dynamic system may have to be controlled by discrete-valued signals due to the inclusion of actuators that are driven by ON/OFF or network with capacity limitations. In such a case, a good output may be obtained by converting continuous-valued input to discrete-valued input with a quantizer designed by NQLib.\r\n\r\n## Install\r\n\r\nYou can install NQLib by using pip\r\n\r\n```sh\r\npip install nqlib\r\n```\r\n\r\nor conda.\r\n\r\n```sh\r\nconda install -c conda-forge nqlib\r\n```\r\n\r\n## Documentation\r\n\r\nAll the documentation is available at \u003ca href=\"https://knttnk.github.io/NQLib/\" target=\"_blank\"\u003eNQLib documentation page\u003c/a\u003e.\r\n\r\nExamples of usage are available at \u003ca href=\"https://colab.research.google.com/drive/1Ui-XqaTZCjwqRXC3ZeMeMCbPqGxK9YXO\" target=\"_blank\"\u003eexample (Google Colab)\u003c/a\u003e.\r\n\r\n## References\r\n\r\nNQLib is a Python library version of \u003ca href=\"https://github.com/rmorita-jp/odqtoolbox\" target=\"_blank\"\u003eODQ Toolbox\u003c/a\u003e,\r\nwhich were developed in \u003ca href=\"https://www.mathworks.com/products/matlab.html\" target=\"_blank\"\u003eMATLAB\u003c/a\u003e.\r\n\r\nThe algorithms used in NQLib are based on the following paper.\r\n\r\n- [1] S. Azuma and T. Sugie: Synthesis of optimal dynamic quantizers for discrete-valued input control;IEEE Transactions on Automatic Control, Vol. 53,pp. 2064–2075 (2008)\r\n- [2] S. Azuma, Y. Minami and T. Sugie: Optimal dynamic quantizers for feedback control with discrete-level actuators; Journal of Dynamic Systems, Measurement, and Control, Vol. 133, No. 2, 021005 (2011)\r\n- [3] 南，加嶋：システムの直列分解に基づく動的量子化器設計；計測自動制御学会論文集，Vol. 52, pp. 46–51(2016)\r\n- [4] R. Morita, S. Azuma, Y. Minami and T. Sugie: Graphical design software for dynamic quantizers in control systems; SICE Journal of Control, Measurement, and System Integration, Vol. 4, No. 5, pp. 372-379 (2011)\r\n- [5] Y. Minami and T. Muromaki: Differential evolution-based synthesis of dynamic quantizers with fixed-structures; International Journal of Computational Intelligence and Applications, Vol. 15, No. 2, 1650008 (2016)\r\n\r\n## License\r\n\r\nThis software is released under the MIT License, see LICENSE.txt.\r\n\r\n## How to Cite NQLib\r\n\r\nIf you use NQLib, please support the project by citing the paper according to the steps below. This encourages further development and leads to more frequent updates.\r\n\r\n1. Head to [the repository of NQLib](https://github.com/knttnk/NQLib).\r\n2. Click on the \"Cite this repository\" button on the right side of the page.\r\n3. Follow the instructions to generate a citation in your preferred format.\r\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fknttnk%2Fnqlib","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fknttnk%2Fnqlib","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fknttnk%2Fnqlib/lists"}