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Trajectory Tracking Using Frenet Coordinates with Deep Deterministic Policy Gradient

Autor: Jiang, Tongzhou, Liu, Lipeng, Jiang, Junyue, Zheng, Tianyao, Jin, Yuhui, Xu, Kunpeng

This paper studies the application of the DDPG algorithm in trajectory-tracking tasks and proposes a trajectorytracking control method combined with Frenet coordinate system. By converting the vehicle's position and velocity information from the Cart

Externí odkaz: http://arxiv.org/abs/2411.13885

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Artistic Neural Style Transfer Algorithms with Activation Smoothing

Autor: Li, Xiangtian, Cao, Han, Zhang, Zhaoyang, Hu, Jiacheng, Jin, Yuhui, Zhao, Zihao

The works of Gatys et al. demonstrated the capability of Convolutional Neural Networks (CNNs) in creating artistic style images. This process of transferring content images in different styles is called Neural Style Transfer (NST). In this paper, we

Externí odkaz: http://arxiv.org/abs/2411.08014

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Application of an ANN and LSTM-based Ensemble Model for Stock Market Prediction

Autor: Liu, Fang, Guo, Shaobo, Xing, Qianwen, Sha, Xinye, Chen, Ying, Jin, Yuhui, Zheng, Qi, Yu, Chang

Stock trading has always been a key economic indicator in modern society and a primary source of profit for financial giants such as investment banks, quantitative trading firms, and hedge funds. Discovering the underlying patterns within the seeming

Externí odkaz: http://arxiv.org/abs/2410.20253

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Central Limit Theorem on the Conjugacy Measure of Symmetric Groups

Autor: Jin, Yuhui

Regarding the conjugacy representation on symmetric groups, we initiate a normalized measure emerging from this representation, namely the conjugacy measure. A central limit theorem for character ratios of random representations of the symmetric grou

Externí odkaz: http://arxiv.org/abs/2407.09824

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GraphCNNpred: A stock market indices prediction using a Graph based deep learning system

Autor: Jin, Yuhui

The application of deep learning techniques for predicting stock market prices is a prominent and widely researched topic in the field of data science. To effectively predict market trends, it is essential to utilize a diversified dataset. In this pa

Externí odkaz: http://arxiv.org/abs/2407.03760

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On the Hecke Module of $\text{GL}_n(k[[z]])\backslash \text{GL}_n(k((z)))/\text{GL}_n(k((z^2)))$

Autor: Jin, Yuhui

Every double coset in $\text{GL}_m(k[[z]])\backslash \text{GL}_m(k((z)))/\text{GL}_m(k((z^2)))$ is uniquely represented by a block diagonal matrix with diagonal blocks in $\{1,z, \begin{pmatrix} 1& z\\ 0 &z^i \end{pmatrix} (i>1)\}$ if $char(k) \neq 2

Externí odkaz: http://arxiv.org/abs/2406.19017

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