JP2021536078A - 復号のための方法、コンピュータプログラム製品、及びデバイス - Google Patents
復号のための方法、コンピュータプログラム製品、及びデバイス Download PDFInfo
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Abstract
Description
送信機の送信方式の部分であって、この送信方式の部分はエンコーダEに後続する、送信方式の部分と、
無線通信チャネルと、
を表す第2の変換を、それぞれベクトル
τlは、実数であり、if l≠l’=>τl≠τl’である。
A及びBlは、実数である。
Kは、3以上の正の整数である。
受信モジュールと、
デコーダと、
を備え、上記デコーダは、人工ニューラルネットワークシステムを含み、人工ニューラルネットワークシステムの少なくとも活性化関数は、複数レベル活性化関数である、デバイスに関する。
−
−基本領域内で点P’’1に最も近い格子点C1を求めることと、
−
によって処理することができる。
点P’が最も近いのかを判断しなければならない。そのために、格子デコーダは、基本領域(又はベクトル
A及びBlは、実数である。Kは、
Claims (13)
- 前記エンコーダEの入力は、変調エンコーダの出力に接続される、請求項1〜5のいずれか1項に記載の方法。
- mが1〜MNである関数fm Nのうちの少なくとも1つは、複数レベル活性化関数である、請求項6に記載の方法。
- 前記エンコーダEは、格子エンコーダを含み、前記格子エンコーダの入力は、前記エンコーダEの入力である、請求項1〜8のいずれか1項に記載の方法。
- mが1〜Miであり、iが1〜N−1である関数fm iのうちの少なくとも1つは、複数レベル活性化関数である、請求項9に記載の方法。
- 前記エンコーダEは、MIMOエンコーダを含む、請求項1〜10のいずれか1項に記載の方法。
- プロセッサによって実行されると、請求項1〜11のいずれか1項に記載の方法を実行するコード命令を含むコンピュータプログラム製品。
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EP18306413.8 | 2018-10-29 | ||
EP18306413.8A EP3648012A1 (en) | 2018-10-29 | 2018-10-29 | Multilevel activation function for deep neural networks |
PCT/JP2019/034317 WO2020090214A1 (en) | 2018-10-29 | 2019-08-26 | Method for decoding, computer program product, and device |
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US11625610B2 (en) * | 2019-03-12 | 2023-04-11 | Samsung Electronics Co., Ltd | Multiple-input multiple-output (MIMO) detector selection using neural network |
US11604976B2 (en) * | 2020-04-29 | 2023-03-14 | International Business Machines Corporation | Crossbar arrays for computations in memory-augmented neural networks |
CN113364535B (zh) * | 2021-05-28 | 2023-03-28 | 西安交通大学 | 数学形式多输入多输出检测方法、系统、设备及存储介质 |
CN113627598B (zh) * | 2021-08-16 | 2022-06-07 | 重庆大学 | 一种用于加速推荐的孪生自编码器神经网络算法及系统 |
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JP2013500660A (ja) * | 2009-07-28 | 2013-01-07 | エコール・ポリテクニーク・フェデラル・ドゥ・ローザンヌ (ウ・ペ・エフ・エル) | 情報の符号化および復号 |
JP2018518126A (ja) * | 2015-11-04 | 2018-07-05 | 三菱電機株式会社 | チャネルを介して送信されたシンボルを復号するための方法及び受信器 |
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CA2063103A1 (en) * | 1992-03-16 | 1993-09-17 | Ynjiun P. Wang | Systems for encoding and decoding data in machine readable graphic form |
US7023936B2 (en) * | 2001-10-29 | 2006-04-04 | Intel Corporation | Method and apparatus for decoding lattice codes and multilevel coset codes |
GB2398976B (en) * | 2003-02-28 | 2006-03-08 | Samsung Electronics Co Ltd | Neural network decoder |
US8116399B2 (en) * | 2008-01-31 | 2012-02-14 | Hui Long Fund Limited Liability Company | Multiple-input multiple-output signal detectors based on relaxed lattice reduction |
US8605808B2 (en) * | 2008-02-29 | 2013-12-10 | Indian Institute Of Science | Method to detect data transmitted by multiple antennas |
US8040981B2 (en) * | 2008-07-10 | 2011-10-18 | Xilinx, Inc. | Symbol detection in a MIMO communication system |
KR101753618B1 (ko) * | 2011-02-11 | 2017-07-04 | 삼성전자주식회사 | 릴레이 노드를 이용한 멀티 노드 간 양방향 통신 방법 및 장치 |
US8718170B2 (en) * | 2011-09-12 | 2014-05-06 | Daniel Nathan Nissani (Nissensohn) | Lattice coded mimo transmission method and apparatus |
US9184876B2 (en) * | 2014-02-19 | 2015-11-10 | Mitsubishi Electric Research Laboratories, Inc. | Method and apparatus for detecting symbols received wirelessly using probabilistic data association with uncertainty |
US10878583B2 (en) * | 2016-12-02 | 2020-12-29 | Google Llc | Determining structure and motion in images using neural networks |
CN107609638B (zh) * | 2017-10-12 | 2019-12-10 | 湖北工业大学 | 一种基于线性编码器和插值采样优化卷积神经网络的方法 |
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BOURAS D P ET AL.: "Neural-net based receiver structures for single- and multi-amplitude signals in interference channel", PROCEEDINGS OF IEEE WORKSHOP ON NEURAL NETWORKS FOR SIGNAL PROCESSING, JPN6022014079, September 1994 (1994-09-01), pages 535 - 544, XP010125535, ISSN: 0004749325, DOI: 10.1109/NNSP.1994.366012 * |
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CN112889074A (zh) | 2021-06-01 |
CN112889074B (zh) | 2024-07-02 |
EP3648012A1 (en) | 2020-05-06 |
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