检索结果-内蒙古大学图书馆

MRLCD-A: Lag-aware alignment for multivariate time series forecasting in multiple scenarios

Information processing and Management 2025年第5期62卷

作者： Sun, Dezhi Qin, Jiwei Zhang, Zihao Qin, Xizhong Zhang, Huiguo School of Computer Science and Technology Xinjiang University Xinjiang Uygur Autonomous Region Urumqi 830046 China Xinjiang Key Laboratory of Signal Detection and Processing Xinjiang University Urumqi830046 China School of Mathematics and System Science Xinjiang University Xinjiang Uygur Autonomous Region Urumqi 830046 China

In multivariate time series forecasting tasks, the varying degrees of lag relationships among multivariate data significantly increase the complexity of accurate predictions. A model must effectively capture long-term dependencies and address intricate lag correlations to achieve reliable long-term forecasting. This paper proposes a novel Multivariate Rolling Lag Correlation Detection-Alignment (MRLCD-A) method to tackle these challenges. The method identifies rolling correlations, calculates lag distances in multivariate sequence inputs, and aligns the lagged variables accordingly. Multivariate Time Series (MTS) forecasting uses a Channel Dependency (CD) approach. Experiments on time series datasets across various scenarios, including electricity, weather, exchange rates, and atmospheric carbon concentrations, demonstrate that the proposed method outperforms state-of-the-art models in forecasting general multivariate time series and predicting long-term time series data in real-world environments. © 2025 Elsevier Ltd

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

Stable Extended U-Net for Noise-Robust Speaker Verification

Stable Extended U-Net for Noise-Robust Speaker Verification

引用

International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Zonghui Wang Zhihua Fang Liang He School of Computer Science and Technology Xinjiang University Urumqi China Xinjiang Key Laboratory of Signal Detection and Processing Urumqi China School of Intelligence Science and Technology Xinjiang University Urumqi China Department of Electronic Engineering Tsinghua University Beijing China Beijing National Research Center for Information Science and Technology Tsinghua University Beijing China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

With advancements in deep learning, speaker verification systems have significantly improved their performance in noisy environments. Researchers typically demonstrate the effectiveness of their improved models by comparing performance on specific datasets, such as the VoxCeleb benchmark. However, in diverse real-world noise conditions, the out-of-domain generalization ability is also a crucial factor in evaluating a model’s performance improvement. Research on stable learning indicates that eliminating the spurious correlation between training and testing data can enhance the generalization of the model. Building on this idea, we propose an improved speaker verification system with high generalization based on the extended U-Net (ExU-Net). It uses the sample reweighting method from stable learning to eliminate sample correlations and retains more effective speaker information through subpixel convolutions and coordinate attention mechanisms. We validate the effectiveness of this approach through extensive evaluations on VoxCeleb1, VOiCES, and other out-of-domain noise test sets, highlighting its generalization capability and model robustness.

关键词： Training Correlation Attention mechanisms Convolution Data models Stability analysis Robustness Noise measurement Speech processing signal to noise ratio

来源：评论

学校读者我要写书评

暂无评论

Conditional Privacy-Preserving Transaction for the Unspent Transaction Output-Based Multi-Chain Blockchain System

引用

IEEE Transactions on Computers 2025年

作者： Cui, Jie Zhuang, Wenting Zhong, Hong Zhang, Qingyang Wang, Fengqun He, Debiao Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Hefei230039 China Anhui University Anhui Engineering Laboratory of IoT Security Technologies Hefei230039 China Wuhan University School of Cyber Science and Engineering Wuhan430072 China MatrixElements Technologies Shanghai Key Laboratory of Privacy Preserving Computation Shanghai201204 China

The anonymity of blockchain may be exploited by criminals for illegal fund transfers, thus a conditional privacy-preserving scheme is important for blockchain regulation. Currently, sharding technology under a multi-chain architecture is used to improve blockchain scalability. However, current conditional privacy-preserving schemes cannot work on this architecture. To protect the privacy of the transaction, we present a conditional privacy-preserving transaction scheme (MC-CPPT) for multi-chain blockchain system. In this system, we proposed a zero-knowledge proof based anonymous transaction, in terms of the identities of transaction participants and amounts, which also enables the unlinkability of transactions and indistinguishability between cross-chain and intra-chain transactions in multi-chain blockchain system. In addition, a multi-node regulatory agency is introduced to control the transaction amount and frequency in the system without a single point of failure. Moreover, an ECC-based encryption scheme is proposed to achieve the traceability of suspicious transactions. A security model is defined and the security of MC-CPPT is demonstrated to meet the expected security goals. Evaluating the prototype revealed acceptable performance and additional security features. © 1968-2012 IEEE.

关键词： Anonymity

来源：评论

学校读者我要写书评

暂无评论

Experimental analysis of sea clutter using airborne circular scanning SAR in medium grazing angle

引用

Journal of Systems Engineering and Electronics 2019年第1期30卷 68-77页

作者： PAN Xueli LIAO Guisheng YANG Zhiwei DANG Hongxing National Laboratory of Radar Signal Processing Xidian University Academy of Space Electronic Information Technology

The theoretical statistical model of sea clutter is a key issue for maritime surveillance. In recent years, the statistical model of sea clutter has attracted much attention to design the detector well. Meanwhile, the circular scanning synthetic aperture radar(SAR) has been applied to wide surveillance of the sea ***, the paper analyzes the validity of available sea clutter models for range Doppler images from different scan angles for moderate sea state in the medium grazing angle. The parameter estimation method for different distribution models employs the method of logarithmic cumulant(MoLC) based on Mellin transform uniformly. By the analysis of the fitting performance between the histogram of real data and the amplitude probability density function(PDF) of empirical distribution models and the goodness-of-fit(GoF) test for real data from different scan angles, it is indicated the generalized K(GK) distribution with generalized Gamma texture distribution can fit the sea clutter well for different scan angles in the medium grazing angle.

关键词： range Doppler image method of logarithmic cumulant (MoLC) Mellin transform generalized Gamma distribution.

来源：评论

学校读者我要写书评

暂无评论

Mining and Harvesting High Quality Topical Resources from the Web

引用

Chinese Journal of Electronics 2016年第1期25卷 48-57页

作者： ZHAO Wei GUAN Ziyu CAO Zhengwen LIU Zheng National Laboratory of Radar Signal Processing Xidian University College of Information and Technology Northwest University of China

Focused crawlers aim to effectively prioritize uncrawled URLs to harvest relevant pages while avoiding irrelevant ones. In practice, harvesting high quality topical Web resources is more important due to the explosion of Web information. Our study shows that the popular focused crawling strategy cannot achieve this *** this paper we develop a new focused crawler, namely On-line topical quality estimation(OTQE), which intelligently evaluates the topical quality of uncrawled pages by the observed link and content evidences and prioritize their URLs accordingly. The new crawler is scalable and requires fewer additional resources to do link-based analysis. The experimental results on crawling 3.6 million Web pages demonstrate the advantages of our proposed method over traditional focused crawlers.

关键词： Focused crawling Topical crawlers Clas sification Open directory project

来源：评论

学校读者我要写书评

暂无评论

TOEformer: Temporal order enhanced Transformer for time series forecasting

引用

Engineering Applications of Artificial Intelligence 2025年 155卷

作者： Li, Qiang Qin, Jiwei Wang, Dacheng Qin, Xizhong Cui, Daishun Xie, Jiachen Sun, Dezhi School of Computer Science and Technology Xinjiang University Urumqi China Xinjiang Key Laboratory of Signal Detection and Processing Xinjiang University Urumqi China Aerospace Information Research Institute Chinese Academy of Sciences Beijing China

Transformers have shown excellent performance in time series forecasting, but a recent study points out that existing Transformer-based time series forecasting models cannot preserve temporal order well. To address this problem, we preserve temporal order information by integrating linear and Transformer structures and predicting trend and seasonal data, respectively, which compensates for the inadequacy of the Transformer in this regard by leveraging linear models to preserve the temporal order information of the original sequence. Besides, directly combining the seasonal and trend part prediction results increases the overall prediction error. For this problem, this paper proposes a new loss function, the relative value exponential loss, which reduces the impact of the problem on predictions by constraining the network to generate more seasonal-trend pairs that can offset each other's errors. Experimental results on six benchmark public datasets show that our temporal order enhanced Transformer (TOEformer) can preserve temporal order information and produce better forecasting performance in more than 85% of multivariate prediction setups compared to state-of-the-art time series forecasting models. The proposed relative value exponential loss effectively mitigates the overall error growth problem. © 2025

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

A Singing Melody Extraction Network Via Self-Distillation and Multi-Level Supervision

A Singing Melody Extraction Network Via Self-Distillation an...

引用

International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Ying Hu Jiabo Jing Fan Li Lijun He Li Lin Wenzhong Yang Key Laboratory of Signal Detection and Processing Urumqi China School of Computer Science and Technology Xinjiang University Urumqi China School of Information and Communications Engineering Xi’an Jiaotong University Xi’an China Xinjiang Institute of Electronics Research Shares Co. Ltd Urumgi China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Extracting singing melody from polyphonic music is an important topic in the field of music information retrieval. In this paper, we propose a singing melody extraction network consisting of five stacked multi-scale feature time-frequency aggregation (MF-TFA) modules. In the same network, deeper layers generally contain more contextual information than shallower layers. To help the shallower layers enhance the ability of task-relevant feature extraction, we propose a self-distillation and multi-level supervision (SD-MS) method, which leverages the feature distillation from the deepest layer to the shallower one and multi-level supervision to guide network training. Visualization analysis shows that by introducing SD-MS, the same-level layer in the network can obtain a clearer representation of fundamental frequency components, while the shallower layers can even learn more task-relevant semantic information. Ablation study results indicate that SD-MS applies to existing melody extraction models and can consistently improve performance. Experimental results show that our proposed method, MF-TFA with SD-MS, outperforms six compared state-of-the-art methods, achieving overall accuracy (OA) scores of 87.1%, 89.9%, and 76.6% on the ADC 2004, MIREX 05, and MEDLEY DB datasets, respectively. The main code will be available at https://***/SmoothJing/MF-TFA_SD-MS.

关键词： Training Visualization Time-frequency analysis Semantics signal processing Feature extraction Multiple signal classification Data mining Speech processing Music information retrieval

来源：评论

学校读者我要写书评

暂无评论

ZCS-CDiff: A Zero-Shot Code-Switching TTS System with Conformer-Based Diffusion Model

ZCS-CDiff: A Zero-Shot Code-Switching TTS System with Confor...

引用

International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Ke Chen Zhihua Huang Liang He Yonghong Yan School of Computer Science and Technology Xinjiang University Urumqi China Xinjiang Key Laboratory of Signal Detection and Processing Urumqi China Department of Electronic Engineering Tsinghua University Beijing China University of Chinese Academy of Sciences Beijing China Key Laboratory of Speech Acoustics and Content Understanding Institute of Acoustics CAS Beijing China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Code-Switching (CS) Text-To-Speech (TTS) models have gained attention due to the increasing prevalence of multilingual communication. However, existing models struggle to meet the growing demand for personalized CS TTS, particularly in Zero-Shot (ZS) scenarios where the model should generate speech for an unseen speaker from reference speech. In this paper, we propose ZCS-CDiff, a zero-shot code-switching TTS system with the Conformer-based diffusion model. We disentangle speech features and use the diffusion model to precisely model these disentangled attributes, resulting in high-quality ZS CS speech. Additionally, we introduce a Conformer-based WaveNet as the denoising network within the diffusion model to further improve the accuracy of modeling different attributes. We also designed a speaker-assist module to help the model better handle speaker information extracted from the reference speech, resulting in CS speech with higher speaker similarity. Experimental results and ablation studies demonstrate that the ZS CS speech generated by ZCS-CDiff has good speech naturalness, intelligibility, and speaker similarity while confirming the effectiveness of our design choices. Audio samples are available 1 .

关键词： Training Adaptation models Accuracy Speech coding Noise reduction Speech enhancement signal processing Diffusion models Probabilistic logic Text to speech

来源：评论

学校读者我要写书评

暂无评论

SFUnet-DCNN: An effective approach for LPI radar waveform recognition under low SNR conditions

引用

IEEE Sensors Journal 2025年

作者： Chen, Yi Quan, Daying Yu, Kaiyin Wang, Xiaofeng Jin, Ning Xing, Mengdao Wu, Jiongfeng China Jiliang University School of Information Engineering Hangzhou310000 China Xidian University National Key Laboratory of Radar Signal Processing Xi’an710071 China Xidian University Collaborative Innovation Center of Information Sensing and Understanding Xi’an710071 China Xidian University Academy of Advanced Interdisciplinary Research Xi’an710071 China Zhejiang Chitic-Safeway New Energy Technology Co. Ltd Hangzhou310000 China

Low Probability of Intercept (LPI) radar waveform recognition is crucial in modern electronic defense, providing decision-makers with essential insights. However, LPI radar signals are highly susceptible to noise interference, especially in low signal-to-Noise Ratio (SNR) environments, significantly reducing recognition accuracy. To address this challenge, we propose a novel LPI radar waveform recognition approach called SFUnet-DCNN, which can achieve robust recognition performance under low SNR scenarios. First, the LPI radar signals are transformed into Time-Frequency Images (TFIs) using the Choi-Williams Distribution (CWD). Subsequently, the TFIs at various SNR levels are fed into a Deep Convolutional Neural Network (DCNN) with Spatial Frequency Blocks (SFBs), which extracts effective features for the SNR estimation and the residual attention classification network. The SFUnet denoising network is activated specifically to reconstruct low SNR TFIs, which are then reprocessed by the DCNN. Finally, the residual attention classification network generates modulation-type predictions. Extensive simulation experiments demonstrate the impressive recognition performance of our approach compared with State-Of-The-Art (SOTA) baselines. Remarkably, even at an SNR of -10 dB, it achieves an overall recognition accuracy of up to 95%. Furthermore, we have verified the effectiveness of the proposed model using actual measurement data, emphasizing its practical applicability, which confirms that the proposed approach is a powerful tool for enhancing radar signal recognition in challenging environments. © 2001-2012 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Optically transparent transmissive orbital angular momentum (OAM) metasurface with high transmittance and broadband characteristics

引用

Optics Express 2025年第12期33卷 24385-24395页

作者： Yong Cai Yuying Dai Yue Ma Gang Wang Guanghui Xu Xingang Ren Hui Wang Xiaohu Zhao Xianliang Wu Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui University Hefei 230039 China Key Laboratory of Electromagnetic Environmental Sensing of Anhui Higher Education Institutes Anhui University Hefei 230039 China wang_toward@*** ghxu86@*** Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Institute of Physical Science and Information Technology Anhui University Hefei 230039 China xgren@*** Hefei Normal University Hefei 230009 China

This work proposes a high-performance broadband orbital angular momentum (OAM) beam-generating metasurface based on optically transparent media. A broadband polarization-converting transmissive metasurface, which operates in the 18 - 24 (28.57% fractional bandwidth) GHz range, has been realized by collaboratively designing dual C-split ring resonator structures and bidirectional lattice-patterned surface networks. The array structure demonstrates typical helical phase distribution features in the K-band, and experimental results verify simulation design. Innovatively employing a composite structure of quartz glass substrate and patterned conductive thin films, the design achieves compatible optimization of 77% visible-light transmittance and microwave broadband performance. This approach breaks through the mutually exclusive limitations of traditional metasurfaces’ optical/electromagnetic properties, providing a highly integrated solution for transparent antenna radomes in satellite communication systems and multi-mode beam multiplexing applications.

关键词： Orbital angular momentum multiplexing Phase plates Ring resonators Spatial light modulators Spiral phase Thin films

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：