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Advancements in Intelligent Photonics: The Role of Silicon Photonics and Phase Change Materials in High-Efficiency Computing 15

Advancements in Intelligent Photonics: The Role of Silicon P...

引用

15th International Conference on Information Optics and Photonics, CIOP 2024

作者： Yun, Yiting Xu, Kai Wang, Weiquan Wei, Maoliang Li, Junying Chen, Zequn Li, Lan Lin, Hongtao The State Key Lab of Brain-Machine Intelligence Key Laboratory of Micro-Nano Electronics and Smart System of Zhejiang Province College of Information Science and Electronic Engineering Zhejiang University Zhejiang Hangzhou310027 China Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Zhejiang Hangzhou310024 China Key Laboratory of 3D Micro/Nano Fabrication and Characterization of Zhejiang Province School of Engineering Westlake University Zhejiang Hangzhou310030 China

ISBN: (数字)9781510686175

ISBN: (纸本)9781510686168

Intelligent photonics, driven by silicon photonics, is revolutionizing high-speed data processing, low-power computing, and precision sensing. Leveraging these advances, photonic chips are enabling the development of optical neural networks and nonlinear activation mapping, which are crucial for addressing the demands of large generative models. However, traditional on-chip control methods struggle with high power consumption and volatility. To overcome these challenges, phase-change materials(PCMs) offer high optical contrast and non-volatility, enhancing integration density and reducing power usage. This article discusses the performance and reversible control of PCMs and their integration with silicon photonics. By incorporating PCMs into in-memory optical computing chips, we achieved 4-bit storage and over 88% accuracy on the MNIST dataset, marking significant progress in next-generation high-performance computing. © 2024 SPIE.

关键词： Silicon photonics

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Advanced absolute orientation algorithm based on unit quaternion on alignment

Advanced absolute orientation algorithm based on unit quater...

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International Conference on Information and Automation (ICIA)

作者： Baoling Qin Xiuzhi Li Songmin Jia Ailin Yang Huan Qiu College of Electronic and Control Engineering Beijing University of Technology Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China

The main objective of this paper is to develop 3D point cloud alignment technique by using an improved absolute orientation algorithm based on unit quaternion. In this method, Scale Invariant Features Transform (SIFT) is used to find corresponding feature points, and Random Sample Consensus (RANSAC) is used as robust estimator to remove false matches in the point cloud group. The unit quaternion solution is employed for initial registration. After the initial registration of point clouds, this cannot meet the requirements of registration accuracy. Therefore, we need to achieve accurate registration on the basis of initial registration. The Iterative Closest Point (ICP) algorithm is one of the widely-used methods to cope with 3D registration. However, ICP is vulnerable to outliers and missing data, which severely compromises its performance. In this paper, Sparse L p -norm based ICP algorithm is developed to achieve precise registration. Experimental results verified accuracy of the presented algorithm in point cloud registration.

关键词： Three-dimensional displays Quaternions Iterative closest point algorithm Accuracy Optimization Mathematical model Matrix decomposition

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Natural Gas Load Forecasting Based on Multi-Stage Model Identification 14

Natural Gas Load Forecasting Based on Multi-Stage Model Iden...

引用

14th IEEE International Conference on Cyber Technology in Automation, control, and Intelligent systems, CYBER 2024

作者： Zhang, Pengbin Wang, Hongrui Xing, Kunpeng Yuan, Mingzhe Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Chinese Academy of Sciences Key Laboratory of Networked Control System Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Guangzhou Institute of Industrial Intelligence Guangzhou511458 China China Nuclear Power Engineering Co. Ltd. Shenzhen518124 China

ISBN: (纸本)9798331506056

Natural gas load forecasting is crucial for the safe operation of urban natural gas. Based on the system identification method, the short-term natural gas load forecasting is studied in the paper. Employing a multi-stage identification framework, the initial values of the model parameters using the least squares and the instrumental variables method, while the model parameters are further optimized by the prediction error method to improve the accuracy of the model identification. The proposed method is validated by the simulation based on the public natural gas data in the U.S., demonstrating the algorithm's effectiveness in forecasting the daily natural gas load effectively. © 2024 IEEE.

关键词： Prediction models

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Simulations and Experiments of Time-Varying Takagi Factorization via Zhang Neural Network 5

Simulations and Experiments of Time-Varying Takagi Factoriza...

引用

5th IEEE Advanced Information Technology, Electronic and Automation control Conference, IAEAC 2021

作者： Tang, Zanyu Zeng, Tianyu Li, Zhenyu Chen, Jianrong Zhang, Yunong Sun Yat-sen University School of Computer Science and Engineering Guangzhou510006 China Guangdong Key Laboratory of Modern Control Technology Guangzhou510070 China College of Information Science and Engineering Jishou University Jishou416000 China School of Public Health Administration Youjiang Medical University for Nationalities Baise533000 China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education Guangzhou510006 China

The problem of Takagi factorization (TF) for complex time-varying symmetric matrix is proposed in this paper. To solve this difficult and challenging problem, a continuous-time TF (CTTF) model of derivative equation system form is proposed via Zhang neural network (ZNN) method. For the sake of digital hardware implementation, we also build up the corresponding discrete-time (DT) ZNN solution models with different precisions of the derivative equation system discretization. Specifically, an eight-instant DTTF (EIDTTF) model are proposed. We also comparatively use two other multi-instant (e.g., four-instant and six-instant, i.e., FIDTTF and SIDTTF, respectively) models by discretizing the CTTF model. The effective solution step-size intervals of the proposed DTTF models are further discussed lastly. The results of simulations and experiments substantiate the correctness, effectiveness and superiority of the proposed CTTF and DTTF models. © 2021 IEEE.

关键词： Complex networks

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AoI-Reliability Analysis with Block Length over Erasure Channels Using Rateless Codes 24

AoI-Reliability Analysis with Block Length over Erasure Chan...

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24th IEEE International Conference on Communication Technology, ICCT 2024

作者： Huang, Haobo Fu, Yusun Qiao, Yue Yin, Junpeng Yan, Weiwu Shanghai Jiao Tong University Ningbo Artificial Intelligence Institute Ningbo China Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai China Shanghai Jiao Tong University Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (纸本)9798350363760

As a metric to measure the information freshness, Age of Information (AoI) is widely used to evaluate low-latency high-reliability communication. Since the communication in Industrial Internet of Things (IIoT) often has the special requirements, the relationship among AoI, reliability and block length in time-critical scenarios with bounded latency and non-time-critical scenarios without bounded latency is explored respectively in this paper, based on erasure channels using rateless codes. We build a model using LT codes over erasure channels and consider two metrics: average AoI and bounded AoI. Theoretical analysis and simulation results show that AoI has a minimum value with different block lengths. Furthermore, we draw a conclusion that the minimum value of AoI under different reliability is monotonically decreasing functioned with reliability. Finally, the impact of overhead on reliability and AoI of LT codes in time-critical scenarios is studied. © 2024 IEEE.

关键词： Turbo codes

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A Preliminary Study on the Functional Coupling between Nerve and Blood Microcirculation for Applications in Rehabilitation Robots

A Preliminary Study on the Functional Coupling between Nerve...

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2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023

作者： Li, Qingge Dong, Yuanzhe Zhang, Yuxiang Wang, Xin Jiang, Naifu Huang, Jianping Cui, Han Tian, Lan Zheng, Yue Li, Xiangxin Wang, Lin Li, Guanglin Liang, Wenyuan Peng, Liang Fang, Peng Shenzhen Institute of Advanced Technology Cas Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China University of Chinese Academy of Sciences Shenzhen College of Advanced Technology Shenzhen518055 China National Research Center for Rehabilitation Technical Aids Beijing100176 China Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Institute of Automation Beijing100190 China

ISBN: (纸本)9798350325706

Rehabilitation robots play an important role in the motor function rehabilitation for stroke survivors with hemiplegia. However, the rehabilitation effect of current robots is still limited partly because a single training of motor function can be strongly affected by the decreased blood supply function of the bedridden patients. This work proposed an approach to study the coupling relationship between the motor and blood supply functions by combining the synchronously recorded EEG and cerebral blood oxygen information, where the cerebrations in different movement paradigms were analyzed from an aspect of "functional coupling". The results show that the information of oxyhemoglobin concentration change (ΔHbO) can effectively indicate the cortex activation, and a stronger blood supply is needed in cortexes to perform body movements. The correlations within motor cortexes are significantly stronger than the ones between motor and prefrontal cortexes, and a higher resistance level of extremity training will cause stronger correlations. Calculation of transfer entropy (TE) shows that there exists a bidirectional information transmission between the electrophysiological and blood supply signals, and more information is transmitted always in the direction from ΔHbO to EEG than in the opposite direction. The information transmission or the coupling relationship can be significantly enhanced by extremity movements, and large TE values are achieved in the Theta, Beta and Gamma frequency bands of EEG that correspond to motor functions. This work has demonstrated the functional coupling between nerve and blood microcirculation, which would provide a technical guidance to improve the rehabilitation effect for current robot systems and have great application potentials. © 2023 IEEE.

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Adaptive Positional Encoding for Bundle-Adjusting Neural Radiance Fields

Adaptive Positional Encoding for Bundle-Adjusting Neural Rad...

引用

International Conference on Computer Vision (ICCV)

作者： Zelin Gao Weichen Dai Yu Zhang State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Key Laboratory of Brain Machine Collaborative Intelligence of Zhejiang Province and School of Computer Science Hangzhou Dianzi University Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province

Neural Radiance Fields have shown great potential to synthesize novel views with only a few discrete image observations of the world. However, the requirement of accurate camera parameters to learn scene representations limits its further application. In this paper, we present adaptive positional encoding (APE) for bundle-adjusting neural radiance fields to reconstruct the neural radiance fields from unknown camera poses (or even intrinsics). Inspired by Fourier series regression, we investigate its relationship with the positional encoding method and therefore propose APE where all frequency bands are trainable. Furthermore, we introduce period-activated multilayer perceptrons (PMLPs) to construct the implicit network for the high-order scene representations and fine-grained gradients during backpropagation. Experimental results on public datasets demonstrate that the proposed method with APE and PMLPs can outperform the state-of-the-art methods in accurate camera poses and high-fidelity view synthesis.

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Boltzmann Robust Soliton Distribution for Rateless Codes 24

Boltzmann Robust Soliton Distribution for Rateless Codes

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24th IEEE International Conference on Communication Technology, ICCT 2024

作者： Tang, Jinhui Fu, Yusun Qiao, Yue Yin, Junpeng Huang, Haobo Shanghai Jiao Tong University Ningbo Artificial Intelligence Institute Ningbo China Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai China Shanghai Jiao Tong University Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (纸本)9798350363760

The decoding success rate may be worse when classical degree distributions are used in short-packet transmission of rateless codes, especially in industrial communication scenarios. A novel Boltzmann degree distribution is proposed for Luby Transform (LT) codes. The Boltzmann degree distribution has a high decoding success rate for short-packet transmission but a lower decoding success rate in long-packet transmission. To balance the performance of rateless codes for short and long packet transmission, the Boltzmann degree distribution and the robust soliton distribution (RSD) are combined with a new joint degree distribution, called Boltzmann Robust Soliton Distribution (BRSD). Simulation results show that compared with RSD and Poisson robust soliton distribution (PRSD), the proposed joint distribution can achieve a higher decoding success rate and reduce the average degree, especially in short-packet transmission of industrial communication. © 2024 IEEE.

关键词： Decoding

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Tactile grasp stability classification based on graph convolutional networks

Tactile grasp stability classification based on graph convol...

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2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021

作者： Mi, Tingting Que, Dashun Fang, Senlin Zhou, Zhenning Ye, Chaoxiang Liu, Chengliang Yi, Zhengkun Wu, Xinyu School of Information Engineering Wuhan University of Technology Wuhan430070 China Shenzhen Institute of Advanced Technology CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Shenzhen Key Laboratory of Smart Sensing and Intelligent Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518055 China

ISBN: (纸本)9781665436786

One of the challenges for robots to grasp unknown objects is to predict whether objects will fall at the beginning of grasping. Evaluating robotic grasp state accurately and efficiently is a significant step to address this issue. In this paper, based on the different fusion approaches of multi-sensor tactile signals, we propose two novel methods based on Graph Convolution Network (GCN) for robotic stability classification. Specifically, we propose two deep learning methods including GCN based on data-level fusion (GCN-DF) and GCN based on feature-level fusion (GCN-FF). We explore the optimal parameters for transforming sensor signals into a graph structure. Furthermore, we verify the effectiveness of the proposed methods on the BioTac Grasp Stability (BiGS) dataset. The experimental results prove that the proposed approaches achieve higher classification accuracy than Support Vector machine (SVM) and Long Short-Term Memory (LSTM). © 2021 IEEE.

关键词： Convolution

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Self-organized Criticality in C. elegans Neural Network

Self-organized Criticality in C. elegans Neural Network

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第42届中国控制会议

作者： Xiao Gu Jian Liu Ye Yuan Peng Zhao Kuankuan Xin Tao Fang Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Engineering Research Centre of Intelligent Control and Management Institute of Machine Intelligence University of Shanghai for Science and Technology Queensland Brain Institute The University of Queensland

The self-organized criticality is a fundamental property for organisms to perform normal functional *** large-scale biological neural network researches have found the existence of self-organized criticality through avalanche phenomenon, which is typical characteristic of self-organized criticality. However, such research method is not suitable for small-scale biological neural network, because number of neurons in small-scale biological neural network is not large enough to support the emergence of avalanche phenomenon. It has been demonstrated that branching parameter can also be used to describe the propagation of activity in the neural network. Here, in this paper, the C. elegans neural network composed of 302 neurons is selected to investigate the existence of self-organized criticality using branching parameter. Based on the obtained connectome of C. elegans, a directed graph model is constructed to simulate the gradient potential of neurons and the activity of C. elegans, then, the existence of self-organized criticality in the neural network of C. elegans is proved by using branching parameter method. Meanwhile, the result is further confirmed by analyzing the calcium activity data of C. elegans obtained from biological experiments.

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