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Pyramid–MixNet: Integrate Attention into Encoder-Decoder Transformer Framework for Automatic Railway Surface Damage Segmentation
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作者 Hui Luo Wenqing Li Wei Zeng 《Computers, Materials & Continua》 2025年第7期1567-1580,共14页
Rail surface damage is a critical component of high-speed railway infrastructure,directly affecting train operational stability and safety.Existing methods face limitations in accuracy and speed for small-sample,multi... Rail surface damage is a critical component of high-speed railway infrastructure,directly affecting train operational stability and safety.Existing methods face limitations in accuracy and speed for small-sample,multi-category,and multi-scale target segmentation tasks.To address these challenges,this paper proposes Pyramid-MixNet,an intelligent segmentation model for high-speed rail surface damage,leveraging dataset construction and expansion alongside a feature pyramid-based encoder-decoder network with multi-attention mechanisms.The encoding net-work integrates Spatial Reduction Masked Multi-Head Attention(SRMMHA)to enhance global feature extraction while reducing trainable parameters.The decoding network incorporates Mix-Attention(MA),enabling multi-scale structural understanding and cross-scale token group correlation learning.Experimental results demonstrate that the proposed method achieves 62.17%average segmentation accuracy,80.28%Damage Dice Coefficient,and 56.83 FPS,meeting real-time detection requirements.The model’s high accuracy and scene adaptability significantly improve the detection of small-scale and complex multi-scale rail damage,offering practical value for real-time monitoring in high-speed railway maintenance systems. 展开更多
关键词 Pyramid vision transformer encoder–decoder architecture railway damage segmentation masked multi-head attention mix-attention
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基于时空特征融合的Encoder-Decoder多步4D短期航迹预测 被引量:2
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作者 石庆研 张泽中 韩萍 《信号处理》 CSCD 北大核心 2023年第11期2037-2048,共12页
航迹预测在确保空中交通安全、高效运行中扮演着至关重要的角色。所预测的航迹信息是航迹优化、冲突告警等决策工具的输入,而预测准确性取决于模型对航迹序列特征的提取能力。航迹序列数据是具有丰富时空特征的多维时间序列,其中每个变... 航迹预测在确保空中交通安全、高效运行中扮演着至关重要的角色。所预测的航迹信息是航迹优化、冲突告警等决策工具的输入,而预测准确性取决于模型对航迹序列特征的提取能力。航迹序列数据是具有丰富时空特征的多维时间序列,其中每个变量都呈现出长短期的时间变化模式,并且这些变量之间还存在着相互依赖的空间信息。为了充分提取这种时空特征,本文提出了基于融合时空特征的编码器-解码器(Spatio-Temporal EncoderDecoder,STED)航迹预测模型。在Encoder中使用门控循环单元(Gated Recurrent Unit,GRU)、卷积神经网络(Convolutional Neural Network,CNN)和注意力机制(Attention,AT)构成的双通道网络来分别提取航迹时空特征,Decoder对时空特征进行拼接融合,并利用GRU对融合特征进行学习和递归输出,实现对未来多步航迹信息的预测。利用真实的航迹数据对算法性能进行验证,实验结果表明,所提STED网络模型能够在未来10 min预测范围内进行高精度的短期航迹预测,相比于LSTM、CNN-LSTM和AT-LSTM等数据驱动航迹预测模型具有更高的精度。此外,STED网络模型预测一个航迹点平均耗时为0.002 s,具有良好的实时性。 展开更多
关键词 4D航迹预测 时空特征 encoder-decoder 门控循环单元
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基于encoder-decoder框架的城镇污水厂出水水质预测 被引量:5
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作者 史红伟 陈祺 +1 位作者 王云龙 李鹏程 《中国农村水利水电》 北大核心 2023年第11期93-99,共7页
由于污水厂的出水水质指标繁多、污水处理过程中反应复杂、时序非线性程度高,基于机理模型的预测方法无法取得理想效果。针对此问题,提出基于深度学习的污水厂出水水质预测方法,并以吉林省某污水厂监测水质为来源数据,利用多种结合encod... 由于污水厂的出水水质指标繁多、污水处理过程中反应复杂、时序非线性程度高,基于机理模型的预测方法无法取得理想效果。针对此问题,提出基于深度学习的污水厂出水水质预测方法,并以吉林省某污水厂监测水质为来源数据,利用多种结合encoder-decoder结构的神经网络预测水质。结果显示,所提结构对LSTM和GRU网络预测能力都有一定提升,对长期预测能力提升更加显著,ED-GRU模型效果最佳,短期预测中的4个出水水质指标均方根误差(RMSE)为0.7551、0.2197、0.0734、0.3146,拟合优度(R2)为0.9013、0.9332、0.9167、0.9532,可以预测出水质局部变化,而长期预测中的4个指标RMSE为1.7204、1.7689、0.4478、0.8316,R2为0.4849、0.5507、0.4502、0.7595,可以预测出水质变化趋势,与顺序结构相比,短期预测RMSE降低10%以上,R2增加2%以上,长期预测RMSE降低25%以上,R2增加15%以上。研究结果表明,基于encoder-decoder结构的神经网络可以对污水厂出水水质进行准确预测,为污水处理工艺改进提供技术支撑。 展开更多
关键词 污水厂出水 encoder-decoder 多指标水质预测 GRU模型
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On the Manipulation of the Selectivity of Encoding and Decoding overthe Translator's Subjectivity
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作者 蒋知洋 《海外英语》 2014年第9X期177-178,共2页
The translation activity is a process of the interlinguistic transmission of information realized by the information encoding and decoding.Encoding and decoding,cognitive practices operated in objective contexts,are i... The translation activity is a process of the interlinguistic transmission of information realized by the information encoding and decoding.Encoding and decoding,cognitive practices operated in objective contexts,are inevitably of selectivity ascribing to the restriction of contextual reasons.The translator as the intermediary agent connects the original author(encoder)and the target readers(decoder),shouldering the dual duties of the decoder and the encoder,for which his subjectivity is irrevocably manipulated by the selectivity of encoding and decoding. 展开更多
关键词 encodING and decodING SELECTIVITY COGNITION the TR
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耦合Encoder-Decoder的LSTM径流预报模型研究 被引量:14
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作者 林康聆 陈华 +3 位作者 陈清勇 罗宇轩 刘峰 陈杰 《武汉大学学报(工学版)》 CAS CSCD 北大核心 2022年第8期755-761,共7页
将长短期记忆神经网络(long short-term memory neural network,LSTM)与Encoder-Decoder结构耦合应用为LSTM-ED模型,并与LSTM人工智能径流预报模型进行比较。通过在闽江建溪流域进行应用,结果表明,相较于LSTM,LSTM-ED在检验期整体和各... 将长短期记忆神经网络(long short-term memory neural network,LSTM)与Encoder-Decoder结构耦合应用为LSTM-ED模型,并与LSTM人工智能径流预报模型进行比较。通过在闽江建溪流域进行应用,结果表明,相较于LSTM,LSTM-ED在检验期整体和各预见期具有更高的精度和稳定性,且对于典型洪水的预报洪峰误差更小,其独有的语义向量可以保持水文信息的连续性,预报径流过程不易受降雨波动干扰。2个模型的预报能力都与流域最大汇流时间密切相关,当预见期小于流域最大汇流时间时,2个模型都有很好的预报能力;当预见期大于流域最大汇流时间时,模型预报能力显著变差;当预见期远大于流域最大汇流时间时,2个模型都失去预报可靠性。 展开更多
关键词 径流预报 encoder-decoder结构 长短期记忆神经网络 深度学习 人工神经网络
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基于Encoder-Decoder注意力网络的异常驾驶行为在线识别方法 被引量:3
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作者 唐坤 戴语琴 +2 位作者 徐永能 郭唐仪 邵飞 《兵器装备工程学报》 CAS CSCD 北大核心 2023年第8期63-71,共9页
异常驾驶行为是车辆安全运行的重大威胁,其对人员与物资的安全高效投送造成严重危害。以低成本非接触式的手机多传感器数据为基础,通过对驾驶行为特性进行数据分析,提出一种融合Encoder-Decoder深度网络与Attention机制的异常驾驶行为... 异常驾驶行为是车辆安全运行的重大威胁,其对人员与物资的安全高效投送造成严重危害。以低成本非接触式的手机多传感器数据为基础,通过对驾驶行为特性进行数据分析,提出一种融合Encoder-Decoder深度网络与Attention机制的异常驾驶行为的在线识别方法。该方法由基于LSTM(long short-term memory)的Encoder-Decoder、Attention机制与基于SVM(support vector machine)的分类器3个模块构成。该系统识别方法包括:输入编码、注意力学习、特征解码、序列重构、残差计算与驾驶行为分类等6个步骤。该技术方法利用自然驾驶条件下所采集的手机传感器数据进行实验。实验结果表明:①手机多传感器数据融合方法对驾驶行为识别具备有效性;②异常驾驶行为必然会造成数据异常波动;③Attention机制有助于提升模型学习效果,对所提出模型的识别准确率F1-score为0.717,与经典同类模型比较,准确率得到显著提升;④对于汽车异常驾驶行为来说,SVM比Logistic与随机森林算法具有更优越的识别效果。 展开更多
关键词 异常驾驶 深度学习 编码器-解码器 长短时记忆网络 注意力机制
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LSTM Encoder-Decoder方法预测设备剩余使用寿命 被引量:8
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作者 赵志宏 李晴 +1 位作者 李乐豪 赵敬娇 《交通运输工程学报》 EI CSCD 北大核心 2021年第6期269-277,共9页
应用LSTM Encoder-Decoder提出了机械设备剩余使用寿命预测方法;对获取的传感器数据进行预处理,利用LSTM Encoder对数据序列进行编码,得到设备状态信息的中间表示,其中蕴含了设备状态的特征信息,利用LSTM Decoder对中间表示信息进行解码... 应用LSTM Encoder-Decoder提出了机械设备剩余使用寿命预测方法;对获取的传感器数据进行预处理,利用LSTM Encoder对数据序列进行编码,得到设备状态信息的中间表示,其中蕴含了设备状态的特征信息,利用LSTM Decoder对中间表示信息进行解码,利用解码后的信息预测剩余使用寿命;研究了LSTM Encoder-Decoder方法在公开的C-MAPSS数据集上的剩余使用寿命预测试验,与LSTM、D-LSTM等方法进行了对比试验;研究了不同滑动窗口大小对于剩余寿命预测结果的影响。研究结果表明:LSTM Encoder-Decoder方法的剩余使用寿命预测结果的评分函数值和均方根误差均优于LSTM、D-LSTM方法;在FD001子集上,LSTM Encoder-Decoder方法、LSTM方法和D-LSTM方法对应的均方根误差分别为11、12、16;当滑动窗口大小为30时,LSTM Encoder-Decoder方法在FD001~FD004子集对应的评分函数值分别为164、3 012、372、4 800,对应的均方根误差分别为11、20、14、22;当滑动窗口大小为40时,LSTM Encoder-Decoder方法在FD001~FD004子集对应的评分函数值分别为305、1 220、408、4 828,对应的均方根误差分别为14、16、15、19。可见,提出的LSTM Encoder-Decoder方法是一种有效的预测机械设备剩余使用寿命方法,并且滑动窗口大小对于剩余使用寿命预测结果存在一定的影响。 展开更多
关键词 剩余使用寿命预测 编码器-解码器 LSTM 深度学习 特征提取
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利用Encoder-Decoder框架的深度学习网络实现绕射波分离及成像 被引量:3
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作者 马铭 包乾宗 《石油地球物理勘探》 EI CSCD 北大核心 2023年第1期56-64,共9页
利用单纯绕射波场实现地下地质异常体的识别具有坚实的理论基础,对应的实施方法得到了广泛研究,且有效地应用于实际勘探。但现有技术在微小尺度异常体成像方面收效甚微,相关研究多数以射线传播理论为基础,对于影响绕射波分离成像精度的... 利用单纯绕射波场实现地下地质异常体的识别具有坚实的理论基础,对应的实施方法得到了广泛研究,且有效地应用于实际勘探。但现有技术在微小尺度异常体成像方面收效甚微,相关研究多数以射线传播理论为基础,对于影响绕射波分离成像精度的因素分析并不完备。相较于反射波,由于存在不连续构造而产生的绕射波能量微弱并且相互干涉,同时环境干扰使得绕射波进一步湮没。因此,更高精度的波场分离及单独成像是现阶段基于绕射波超高分辨率处理、解释的重点研究方向。为此,首先针对地球物理勘探中地质异常体的准确定位,以携带高分辨率信息的绕射波为研究对象,系统分析在不同尺度、不同物性参数的异常体情况下绕射波的能量大小及形态特征,掌握绕射波与其他类型波叠加的具体形式;然后根据相应特征性质提出基于深度学习技术的绕射波分离成像方法,即利用Encoder-Decoder框架的空洞卷积网络捕获绕射波场特征,从而实现绕射波分离,基于速度连续性原则构建单纯绕射波场的偏移速度模型并完成最终成像。数据测试表明,该方法最终可满足微小地质异常体高精度识别的需求。 展开更多
关键词 绕射波分离成像 深度神经网络 encoder-decoder框架 方差最大范数
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Brain Encoding and Decoding in fMRI with Bidirectional Deep Generative Models 被引量:2
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作者 Changde Du Jinpeng Li +1 位作者 Lijie Huang Huiguang He 《Engineering》 SCIE EI 2019年第5期948-953,共6页
Brain encoding and decoding via functional magnetic resonance imaging(fMRI)are two important aspects of visual perception neuroscience.Although previous researchers have made significant advances in brain encoding and... Brain encoding and decoding via functional magnetic resonance imaging(fMRI)are two important aspects of visual perception neuroscience.Although previous researchers have made significant advances in brain encoding and decoding models,existing methods still require improvement using advanced machine learning techniques.For example,traditional methods usually build the encoding and decoding models separately,and are prone to overfitting on a small dataset.In fact,effectively unifying the encoding and decoding procedures may allow for more accurate predictions.In this paper,we first review the existing encoding and decoding methods and discuss the potential advantages of a“bidirectional”modeling strategy.Next,we show that there are correspondences between deep neural networks and human visual streams in terms of the architecture and computational rules.Furthermore,deep generative models(e.g.,variational autoencoders(VAEs)and generative adversarial networks(GANs))have produced promising results in studies on brain encoding and decoding.Finally,we propose that the dual learning method,which was originally designed for machine translation tasks,could help to improve the performance of encoding and decoding models by leveraging large-scale unpaired data. 展开更多
关键词 BRAIN encoding and decodING Functional magnetic resonance imaging DEEP neural networks DEEP GENERATIVE models Dual learning
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基于Encoder-Decoder网络的遥感影像道路提取方法 被引量:55
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作者 贺浩 王仕成 +2 位作者 杨东方 王舒洋 刘星 《测绘学报》 EI CSCD 北大核心 2019年第3期330-338,共9页
针对道路目标特点,设计实现了用于遥感影像道路提取的Encoder-Decoder深度语义分割网络。首先,针对道路目标局部特征丰富、语义特征较为简单的特点,设计了较浅深度、分辨率较高的Encoder-Decoder网络结构,提高了分割网络的细节表示能力... 针对道路目标特点,设计实现了用于遥感影像道路提取的Encoder-Decoder深度语义分割网络。首先,针对道路目标局部特征丰富、语义特征较为简单的特点,设计了较浅深度、分辨率较高的Encoder-Decoder网络结构,提高了分割网络的细节表示能力。其次,针对遥感影像中道路目标所占像素比例较小的特点,改进了二分类交叉熵损失函数,解决了网络训练中正负样本严重失衡的问题。在大型道路提取数据集上的试验表明,所提方法召回率、精度和F1-score指标分别达到了83.9%、82.5%及82.9%,能够完整准确地提取遥感影像中的道路目标。所设计的Encoder-Decoder网络性能优良,且不需人工设计提取特征,因而具有良好的应用前景。 展开更多
关键词 遥感 道路提取 深度学习 语义分割 编解码网路
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Blind recognition of k/n rate convolutional encoders from noisy observation 被引量:14
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作者 Li Huang Wengu Chen +1 位作者 Enhong Chen Hong Chen 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2017年第2期235-243,共9页
Blind recognition of convolutional codes is not only essential for cognitive radio, but also for non-cooperative context. This paper is dedicated to the blind identification of rate k/n convolutional encoders in a noi... Blind recognition of convolutional codes is not only essential for cognitive radio, but also for non-cooperative context. This paper is dedicated to the blind identification of rate k/n convolutional encoders in a noisy context based on Walsh-Hadamard transformation and block matrix (WHT-BM). The proposed algorithm constructs a system of noisy linear equations and utilizes all its coefficients to recover parity check matrix. It is able to make use of fault-tolerant feature of WHT, thus providing more accurate results and achieving better error performance in high raw bit error rate (BER) regions. Moreover, it is more computationally efficient with the use of the block matrix (BM) method. © 2017 Beijing Institute of Aerospace Information. 展开更多
关键词 Cognitive radio CONVOLUTION Convolutional codes Error correction Hadamard matrices Hadamard transforms Linear transformations Mathematical transformations Matrix algebra Signal encoding
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基于Encoder-Decoder LSTM的电梯制动滑移量预测方法研究 被引量:2
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作者 苏万斌 江叶峰 +1 位作者 徐彪 易灿灿 《机械制造与自动化》 2022年第6期28-31,共4页
电梯曳引系统的可靠性是电梯安全性能评估中的重要部分,紧急制动滑移量是其重要反映指标,对滑移量进行时序预测能有利保证电梯安全,具有重要意义。采用结合Encoder-Decoder的LSTM模型学习电梯紧急制动滑移量的增长过程,进行多步预测来... 电梯曳引系统的可靠性是电梯安全性能评估中的重要部分,紧急制动滑移量是其重要反映指标,对滑移量进行时序预测能有利保证电梯安全,具有重要意义。采用结合Encoder-Decoder的LSTM模型学习电梯紧急制动滑移量的增长过程,进行多步预测来获得未来区间内滑移预测数据。通过与RNN和LSTM模型预测结果的对比,表明Encoder-Decoder LSTM模型针对电梯紧急制动滑移量的预测具有较好的精度,可以作为电梯曳引能力评估的重要手段。 展开更多
关键词 电梯 LSTM 编码器-解码器 滑移量 时间序列 多步预测
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基于长短时记忆网络的Encoder-Decoder多步交通流预测模型 被引量:25
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作者 王博文 王景升 +3 位作者 王统一 张子泉 刘宇 于昊 《重庆大学学报》 CSCD 北大核心 2021年第11期71-80,共10页
交通流序列多为单步预测。为实现交通流序列的多步预测,提出一种基于编码器解码器(encoder-decoder,ED)框架的长短期记忆网络(long short-term memory,LSTM)模型,即ED LSTM模型。将自回归滑动平均、支持向量回归机、XGBOOST、循环神经... 交通流序列多为单步预测。为实现交通流序列的多步预测,提出一种基于编码器解码器(encoder-decoder,ED)框架的长短期记忆网络(long short-term memory,LSTM)模型,即ED LSTM模型。将自回归滑动平均、支持向量回归机、XGBOOST、循环神经网络、卷积神经网络、LSTM作为对照组进行实验验证。实验结果表明,当预测时间步长增加时,ED框架能够减缓模型性能的下降趋势,LSTM能够充分挖掘时间序列中的非线性关系。除此之外,在单变量输入的情况下,在PEMS-04数据集上,当预测时间步长为t+1到t+12的12个时间步时,ED LSTM模型的均方根误差(root mean squard error,RMSE)及平均绝对误差(mean absolute error,MAE)分别下降0.210~5.422、0.061~0.191。相较于单因素输入,多因素输入的ED LSTM模型在12个预测时间步长下,RMSE、MAE分别下降0.840、0.136。实验证明了ED LSTM模型能够有效地用于交通流序列的多步及单因素、多因素预测任务。 展开更多
关键词 交通流预测 LSTM 编码器解码器 多步预测 深度学习
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Application of Instantaneous Rotational Speed to Detect Gearbox Faults Based on Double Encoders 被引量:2
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作者 Lin Liang Fei Liu +2 位作者 Xiangwei Kong Maolin Li Guanghua Xu 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2019年第1期54-64,共11页
Considerable studies have been carried out on fault diagnosis of gears, with most of them concentrated on conventional vibration analysis. However, besides the complexity of gear dynamics, the diagnosis results in ter... Considerable studies have been carried out on fault diagnosis of gears, with most of them concentrated on conventional vibration analysis. However, besides the complexity of gear dynamics, the diagnosis results in terms of vibration signal are easily misjudged owing to the interference of sensor position or other components. In this paper, an alternative gearbox fault detection method based on the instantaneous rotational speed is proposed because of its advantages over vibration analysis. Depending on the timer/counter-based method for the pulse signal of the optical encoder, the varying rotational speed can be obtained e ectively. Owing to the coupling and meshing of gears in transmission, the excitations are the same for the instantaneous rotational speed of the input and output shafts. Thus, the di erential signal of instantaneous rotational speeds can be adopted to eliminate the e ect of the interference excitations and extract the associated feature of the localized fault e ectively. With the experiments on multistage gearbox test system, the di erential signal of instantaneous speeds is compared with other signals. It is proved that localized faults in the gearbox generate small angular speed fluctuations, which are measurable with an optical encoder. Using the di erential signal of instantaneous speeds, the fault characteristics are extracted in the spectrum where the deterministic frequency component and its harmonics corresponding to crack fault characteristics are displayed clearly. 展开更多
关键词 Instantaneous ROTATIONAL speed Optical encodER Localized fault MULTISTAGE GEARBOX
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Encoding-Decoding-Based Control and Filtering of Networked Systems: Insights, Developments and Opportunities 被引量:3
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作者 Zidong Wang Licheng Wang +1 位作者 Shuai Liu Guoliang Wei 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2018年第1期3-18,共16页
In order to make the information transmission more efficient and reliable in a digital communication channel with limited capacity, various encoding-decoding techniques have been proposed and widely applied in many br... In order to make the information transmission more efficient and reliable in a digital communication channel with limited capacity, various encoding-decoding techniques have been proposed and widely applied in many branches of the signal processing including digital communications, data compression,information encryption, etc. Recently, due to its promising application potentials in the networked systems(NSs), the analysis and synthesis issues of the NSs under various encoding-decoding schemes have stirred some research attention. However, because of the network-enhanced complexity caused by the limited network resources, it poses new challenges to the design of suitable encoding-decoding procedures to meet certain control or filtering performance for the NSs. In this survey paper, our aim is to present a comprehensive review of the encoding-decodingbased control and filtering problems for different types of NSs.First, some basic introduction with respect to the coding-decoding mechanism is presented in terms of its engineering insights,specific properties and theoretical formulations. Then, the recent representative research progress in the design of the encodingdecoding protocols for various control and filtering problems is discussed. Some possible further research topics are finally outlined for the encoding-decoding-based NSs. 展开更多
关键词 encoding-decoding-based communication mechanism encoding-decoding-based control encoding-decodingbased state estimation networked systems
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Determination of optimal period of absolute encoders with single track cyclic gray code 被引量:1
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作者 张帆 朱衡君 《Journal of Central South University》 SCIE EI CAS 2008年第S2期362-366,共5页
Low cost and miniaturized rotary encoders are important in automatic and precise production. Presented here is a code called Single Track Cyclic Gray Code (STCGC) that is an image etched on a single circular track of ... Low cost and miniaturized rotary encoders are important in automatic and precise production. Presented here is a code called Single Track Cyclic Gray Code (STCGC) that is an image etched on a single circular track of a rotary encoder disk read by a group of even spread reading heads to provide a unique codeword for every angular position and features such that every two adjacent words differ in exactly one component, thus avoiding coarse error. The existing construction or combination methods are helpful but not sufficient in determining the period of the STCGC of large word length and the theoretical approach needs further development to extend the word length. Three principles, such as the seed combination, short code removal and ergodicity examination were put forward that suffice determination of the optimal period for such absolute rotary encoders using STCGC with even spread heads. The optimal periods of STCGC in 3 through 29 bit length were determined and listed. 展开更多
关键词 ROTARY encodER ABSOLUTE encodER single track GREY code CYCLIC reliability
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Underwater Object Recognition Based on Deep Encoding-Decoding Network 被引量:4
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作者 WANG Xinhua OUYANG Jihong +1 位作者 LI Dayu ZHANG Guang 《Journal of Ocean University of China》 SCIE CAS CSCD 2019年第2期376-382,共7页
Ocean underwater exploration is a part of oceanography that investigates the physical and biological conditions for scientific and commercial purposes. And video technology plays an important role and is extensively a... Ocean underwater exploration is a part of oceanography that investigates the physical and biological conditions for scientific and commercial purposes. And video technology plays an important role and is extensively applied for underwater environment observation. Different from the conventional methods, video technology explores the underwater ecosystem continuously and non-invasively. However, due to the scattering and attenuation of light transport in the water, complex noise distribution and lowlight condition cause challenges for underwater video applications including object detection and recognition. In this paper, we propose a new deep encoding-decoding convolutional architecture for underwater object recognition. It uses the deep encoding-decoding network for extracting the discriminative features from the noisy low-light underwater images. To create the deconvolutional layers for classification, we apply the deconvolution kernel with a matched feature map, instead of full connection, to solve the problem of dimension disaster and low accuracy. Moreover, we introduce data augmentation and transfer learning technologies to solve the problem of data starvation. For experiments, we investigated the public datasets with our proposed method and the state-of-the-art methods. The results show that our work achieves significant accuracy. This work provides new underwater technologies applied for ocean exploration. 展开更多
关键词 DEEP LEARNING transfer LEARNING encoding-decoding UNDERWATER OBJECT OBJECT recognition
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基于LSTM的Encoder-Decoder多步轨迹预测技术 被引量:7
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作者 李青勇 何兵 +2 位作者 张显炀 朱晓宇 刘刚 《航空兵器》 CSCD 北大核心 2021年第2期49-54,共6页
针对弱约束非合作目标的轨迹特性和运动特性,提出一种基于LSTM的Encoder-Decoder多步轨迹预测技术(EDMTP)。引入一阶差分处理,降低了轨迹数据的时间依赖性,得到了无趋势的轨迹。构造输入输出的轨迹数据对,将预测问题转化为有监督学习问... 针对弱约束非合作目标的轨迹特性和运动特性,提出一种基于LSTM的Encoder-Decoder多步轨迹预测技术(EDMTP)。引入一阶差分处理,降低了轨迹数据的时间依赖性,得到了无趋势的轨迹。构造输入输出的轨迹数据对,将预测问题转化为有监督学习问题,研究多步预测过程中模型性能的变化,实现端到端的轨迹预测。仿真结果表明,该方法能够从历史轨迹数据中提取更多的轨迹特征,在多步轨迹预测中具有明显的优势。与KFTP和HMMTP算法相比,EDMTP的误差增长率分别同比下降了2.18%和3.52%,取得了较好的轨迹预测效果。 展开更多
关键词 轨迹预测 LSTM 编码器-解码器 监督学习 多步预测
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JOINT ITERATIVE DECODING FOR SIMPLE-ENCODING SYSTEMATIC IRREGULAR-LDPC-BASED CODED COOPERATION IN NON-IDEAL RELAY CHANNEL 被引量:3
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作者 Chen Jingwen Yang Fengfan +1 位作者 Luo Lin Tho Le-Ngoc 《Journal of Electronics(China)》 2010年第3期305-315,共11页
In this paper, a new kind of simple-encoding irregular systematic LDPC codes suitable for one-relay coded cooperation is designed, where the proposed joint iterative decoding is effectively performed in the destinatio... In this paper, a new kind of simple-encoding irregular systematic LDPC codes suitable for one-relay coded cooperation is designed, where the proposed joint iterative decoding is effectively performed in the destination which is in accordance with the corresponding joint Tanner graph characterizing two different component LDPC codes used by the source and relay in ideal and non-ideal relay cooperations. The theoretical analysis and simulations show that the coded cooperation scheme obviously outperforms the coded non-cooperation one under the same code rate and decoding complex. The significant performance improvement can be virtually credited to the additional mutual exchange of the extrinsic information resulted by the LDPC code employed by the source and its counterpart used by the relay in both ideal and non-ideal cooperations. 展开更多
关键词 Cooperative communication Low-density parity-check code Relay channel Joint Tanner graph Joint iterative decoding
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Radiation Tolerant Viterbi Decoders for On-Board Processing(OBP) in Satellite Communications 被引量:1
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作者 Zhen Gao Lina Yan +3 位作者 Jinhua Zhu Ruishi Han Ullah Anees Reviriego Pedro 《China Communications》 SCIE CSCD 2020年第1期140-150,共11页
Modern satellite communication systems require on-board processing(OBP)for performance improvements,and SRAM-FPGAs are an attractive option for OBP implementation.However,SRAM-FPGAs are sensitive to radiation effects,... Modern satellite communication systems require on-board processing(OBP)for performance improvements,and SRAM-FPGAs are an attractive option for OBP implementation.However,SRAM-FPGAs are sensitive to radiation effects,among which single event upsets(SEUs)are important as they can lead to data corruption and system failure.This paper studies the fault tolerance capability of a SRAM-FPGA implemented Viterbi decoder to SEUs on the user memory.Analysis and fault injection experiments are conducted to verify that over 97%of the SEUs on user memory would not lead to output errors.To achieve a better reliability,selective protection schemes are then proposed to further improve the reliability of the decoder to SEUs on user memory with very small overhead.Although the results are obtained for a specific FPGA implementation,the developed reliability estimation model and the general conclusions still hold for other implementations. 展开更多
关键词 viterbi decoder on-board processing FPGA user memory fault tolerance single event upsets
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