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The finite field multi-way relay channel with correlated sources: Beyond three users

The finite field multi-way relay channel with correlated sou...

引用

IEEE International Symposium on Information Theory

作者： Lawrence Ong Roy Timo Sarah J. Johnson School of Electrical Engineering and Computer Science University of Newcastle Australia Institute for Telecommunications Research University of South Australia Australia

ISBN: (纸本)9781467325806

The multi-way relay channel (MWRC) models cooperative communication networks in which many users exchange messages via a relay. In this paper, we consider the finite field MWRC with correlated messages. The problem is to find all achievable rates, defined as the number of channel uses required per reliable exchange of message tuple. For the case of three users, we have previously established that for a special class of source distributions, the set of all achievable rates can be found [Ong et al., ISIT 2010]. The class is specified by an almost balanced conditional mutual information (ABCMI) condition. In this paper, we first generalize the ABCMI condition to the case of more than three users. We then show that if the sources satisfy the ABCMI condition, then the set of all achievable rates is found and can be attained using a separate source-channel coding architecture.

关键词： Relays Channel coding Atomic measurements Random variables Mutual information source coding

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Prompt a Robot to Walk with Large Language Models

Prompt a Robot to Walk with Large Language Models

引用

IEEE Conference on Decision and Control

作者： Yen-Jen Wang Bike Zhang Jianyu Chen Koushil Sreenath University of California Berkeley Institute for Interdisciplinary Information Sciences Tsinghua University Shanghai Qi Zhi Institute

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Large language models (LLMs) pre-trained on vast internet-scale data have showcased remarkable capabilities across diverse domains. Recently, there has been escalating interest in deploying LLMs for robotics, aiming to harness the power of foundation models in real-world settings. However, this approach faces significant challenges, particularly in grounding these models in the physical world and in generating dynamic robot motions. To address these issues, we introduce a novel paradigm in which we use few-shot prompts collected from the physical environment, enabling the LLM to autoregressively predict low-level control actions for robots without task-specific fine-tuning. We utilize LLMs as a controller, diverging from the conventional approach of employing them primarily as planners. Simulation experiments across various robots and environments validate that our method can effectively prompt a robot to walk. We thus illustrate how LLMs can function as low-level feedback controllers for dynamic motion control, even in high-dimensional robotic systems. The project website and source code can be found at: ***.

关键词： Legged locomotion Robot motion Grounding Large language models source coding Dynamics Motion control Adaptive control Robots Physics

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A Multiobjective Particle Swarm Optimizer based Localized Feature Selection for Imbalanced Fault Diagnosis

A Multiobjective Particle Swarm Optimizer based Localized Fe...

引用

Congress on Evolutionary Computation

作者： Lin Gao Yu Zhou Hainan Guo Sam Tak Wu Kwong College of Computer Science and Software Engineering Shenzhen University Shenzhen Guangdong China College of Management Shenzhen University Shenzhen Guangdong China Department of Computing and Decision Sciences Lingnan University Hong Kong China

ISBN: (数字)9798350308365

ISBN: (纸本)9798350308372

Modern fault diagnosis faces an imbalance issue at both the sample and feature levels. A common approach is to combine balancing strategies with feature selection algorithms to address this problem. However, this may result in feature subsets that cannot accurately represent the true data distribution. This paper proposes an imbalanced fault diagnosis method called RPLFS-MOBPSO, which combines region purity (RP) with local feature selection to achieve class balance implicitly by partitioning local regions. RP is used as a new objective in the optimization process to achieve accurate fault detection. The adaptive reference point method from Non-Dominated Sorting Genetic Algorithm III is employed to maintain a diverse and evenly distributed external archive. On both the simulated Tennessee Eastma (TE) benchmark datasets and the real bearing experimental bench datasets, the proposed method achieves the best results compared to two LFS methods and four imbalanced ensemble algorithms based on different balancing strategies. Our source codes are available at: https://***/EMRGSZU/papers-code/tree/main/RPLFS-MOBPSO.

关键词： Fault diagnosis Accuracy source coding Fault detection Feature extraction Partitioning algorithms Particle swarm optimization

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LIMI-VC: A Light Weight Voice Conversion Model with Mutual Information Disentanglement

LIMI-VC: A Light Weight Voice Conversion Model with Mutual I...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Liangjie Huang Tian Yuan Yunming Liang Zeyu Chen Can Wen Yanlu Xie Jinsong Zhang Dengfeng Ke Beijing Language and Culture University Baidu (China) Co. Ltd

Voice conversion(VC) model aims to convert the source timbre to the target one. Recently, many VC models utilize pre-trained models to enhance the performance and achieve good results. However, pre-trained models could not somehow disentangle the timbre and linguistic information, thus resulting in a redundancy, which may hurt the conversion performance. In this paper we proposed LIMI-VC, reducing the redundancy between the linguistic content and the timbre information with mutual information disentanglement. We design the model in a light weight form, for the sake of parameter and computation efficiency when pre-trained models are commonly used nowadays. Experiments show that the proposed model can still improve the performance, with 15 times smaller size, compared to baseline. An out-of-domain cross-lingual inference also shows that our model greatly outperforms the baseline. Our source code and audio examples will be available at: https://***/WongLaw/LIMI-VC.

关键词： Training Computational modeling source coding Redundancy Linguistics Signal processing Computational efficiency

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On the variance and the probability of length overflow of lossless codes

On the variance and the probability of length overflow of lo...

引用

IEEE International Symposium on Information Theory

作者： R. Nomura T. Matsushima S. Hirasawa Waseda University Shinjuku Tokyo Japan Aaseda University Shinjuku Tokyo Japan

In this paper, we show the probability of length overflow of several codes by using the variance and the asymptotic normality of the codelength.

关键词： source coding Probability distribution Art

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Secure lossy transmission of vector Gaussian sources

Secure lossy transmission of vector Gaussian sources

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IEEE International Symposium on Information Theory

作者： Ersen Ekrem Sennur Ulukus Department of Electrical and Computer Engineering University of Maryland College Park MD USA

We study the secure lossy transmission of a Gaussian vector source to a legitimate user in the presence of an eaves-dropper, where both the legitimate user and the eavesdropper have Gaussian vector side information. The transmitter describes the source to the legitimate user in a way that the legitimate user can reconstruct the source within a certain distortion while the eavesdropper is kept ignorant of the source as much as possible. We obtain an outer bound for the rate, equivocation and distortion region of this secure lossy transmission problem. This outer bound is tight when the transmission rate constraint is removed. In other words, we obtain the maximum equivocation at the eavesdropper when the legitimate user needs to reconstruct the source within a fixed distortion level while there is no constraint on the transmission rate.

关键词： Markov processes Mutual information Optimization source coding Transmitters Covariance matrix Rate distortion theory

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Fanet: Feature Amplification Network for Semantic Segmentation in Cluttered Background

Fanet: Feature Amplification Network for Semantic Segmentati...

引用

IEEE International Conference on Image Processing

作者： Muhammad Ali Mamoona Javaid Mubashir Noman Mustansar Fiaz Salman Khan MBZUAI UAE Institute of Space Technology Pakistan IBM Research

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

Existing deep learning approaches leave out the semantic cues that are crucial in semantic segmentation present in complex scenarios including cluttered backgrounds and translucent objects, etc. To handle these challenges, we propose a feature amplification network (FANet) as a backbone network that incorporates semantic information using a novel feature enhancement module at multi-stages. To achieve this, we propose an adaptive feature enhancement (AFE) block that benefits from both a spatial context module (SCM) and a feature refinement module (FRM) in a parallel fashion. SCM aims to exploit larger kernel leverages for the increased receptive field to handle scale variations in the scene. Whereas our novel FRM is responsible for generating semantic cues that can capture both low-frequency and high-frequency regions for better segmentation tasks. We perform experiments over challenging real-world ZeroWaste-f [1] dataset which contains background-cluttered and translucent objects. Our experimental results demonstrate the state-of-the-art performance compared to existing methods. The source code can be found at https://***/techmn/fanet.

关键词： Deep learning Semantic segmentation source coding Semantics Task analysis Kernel

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Compress-forward relaying with quantized channel state feedback

Compress-forward relaying with quantized channel state feedb...

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Asilomar Conference on Signals, Systems & Computers

作者： Sha Yao Mikael Skoglund School of Electrical Engineering and ACCESS Linnaeus Center Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)9781424458257

We consider a three-node slowly fading relay channel with a half-duplex relay node. Under short-term power constraints in the source and relay, we investigate the outage exponent of compress-forward relaying with quantized feedback of channel state information from the destination to the relay. In this initial work on this problem, Wyner-Ziv coding is not used at the relay. We show that with only 2-bit of feedback information, most of the gains from knowing the channel state can be obtained.

关键词： Relays State feedback OFDM modulation Fading Channel state information Hydrogen source coding Channel capacity Decoding Performance analysis

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3D Printed Differential Drive Robot with LiDAR and 3D Depth Camera

3D Printed Differential Drive Robot with LiDAR and 3D Depth ...

引用

IEEE International Conference on Control and Robotics Engineering (ICCRE)

作者： Ng Danny Wee-Kiat Kwan Ban-Hoe Chan Siow Cheng Choon-Hian Goh Netizen Robotics Selangor Malaysia Department of Mechatronics and BioMedical Engineering Universiti Tunku Abdul Rahman Kajang Malaysia

ISBN: (数字)9798350372694

ISBN: (纸本)9798350372700

This paper presents the design of a 3D printed mobile differential drive robot with LiDAR and 3D depth sensing. The robot is designed to be low cost and easy to build, making it suitable for educational and research purposes. All the main structures of the robot are 3D printed while the parts used in the robot are from off-the-shelf components. All the design files and source code used in this project is shared in the github repository. The robot is equipped with a LiDAR sensor for mapping and navigation, and a 3D depth sensing camera for object recognition. Robot Operating System (ROS) running on an Intel single board computer serves as the middleware for all robot control operations. The developed robot is able to run simultaneous localization and mapping (SLAM) and perform autonomous navigation. Design files and the software for the robot can be obtained from the github reposi-tory https://***/dannyngweekiat/3D-Printed-Differential-Drive-Bot.

关键词： Three-dimensional displays Laser radar Simultaneous localization and mapping source coding Robot vision systems Robot sensing systems Cameras

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iiPCS: Intent-Based In-Context Learning for Project-Specific Code Summarization

iiPCS: Intent-Based In-Context Learning for Project-Specific...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Yu Wang Xin Liu Xuesong Lu Aoying Zhou East China Normal University Shanghai China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Recent years have witnessed growing research interest in automatic source code summarization due to its beneficial potential in software development and maintenance tasks. In the past few years, various deep learning models have been developed to leverage structural and textual features in the code for generating meaningful and succinct summaries. However, the summaries generated by traditional deep learning models often have syntax errors or are meaningless. The emergence of large language models provides an opportunity to overcome the problem. However, the quality of the summaries largely depends on the in-context learning examples of code-summary pairs. In this work, we develop iiPCS, an LLM-based method for code summarization. We retrieve relevant code-summary pairs as in-context learning examples from the same project of the target code, which ensures to generate more project-specific summaries, and use the predicted intent of the target code to pick few-shot examples, which ensures to generate summaries with the correct intent. Experimental results show that iiPCS can generate code summaries with higher quality compared to traditional methods using deep learning and recent methods using LLMs.

关键词： Deep learning Codes source coding Large language models Semantics Neural networks Syntactics

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