Digital Signal Processing最新文献_第8页

Elemental approximate message passing algorithm for sparse signal recovery 稀疏信号恢复的元素近似消息传递算法

IF 2.9 3区工程技术

Digital Signal Processing Pub Date : 2025-06-19 DOI: 10.1016/j.dsp.2025.105410

Chen Ji , Jisheng Dai , Xue-Qin Jiang , Weichao Xu

引用次数: 0

Design and performance limit of near-field broadband IIR beamformers 近场宽带IIR波束形成器的设计与性能限制

IF 2.9 3区工程技术

Digital Signal Processing Pub Date : 2025-06-19 DOI: 10.1016/j.dsp.2025.105409

Qi He , Zhiguo Feng , Zhibao Li , Ka Fai Cedric Yiu

{"title":"Design and performance limit of near-field broadband IIR beamformers","authors":"Qi He , Zhiguo Feng , Zhibao Li , Ka Fai Cedric Yiu","doi":"10.1016/j.dsp.2025.105409","DOIUrl":"10.1016/j.dsp.2025.105409","url":null,"abstract":"<div><div>This paper considers the design of near-field broadband beamformer based on IIR filters, performing both spatial and frequency filtering. The design problem is formulated as an optimal minimax problem to minimize the error between the desired response and the actual response. To demonstrate the theoretical advantage of the proposed IIR-based beamformer over conventional FIR designs, we introduce a novel performance limit analysis framework in which the filter length is treated as an arbitrary design parameter. This performance limit can be efficiently computed by solving a sequence of functional optimization subproblems. A key theoretical contribution of this work is the proof that both FIR and IIR beamformers converge to the same performance bound. However, the proposed IIR structure achieves this bound with significantly fewer filter coefficients. This finding provides valuable guidance for selecting appropriate filter lengths in practical applications. Furthermore, we propose a novel reduced structure in which all array elements share a common feedback section, offering additional simplification without sacrificing performance. The proposed method is evaluated by means of a room simulation model for various reverberation times. Numerical experiments have shown that the optimal value of the IIR design method can approach the limit faster than FIR-based beamformers, and all reduced structures achieved significant reduction in terms of filter lengths comparing with FIR beamformers in the performance limit.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"167 ","pages":"Article 105409"},"PeriodicalIF":2.9,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144490160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

AED-YOLO11: A small object detection model based on YOLO11 AED-YOLO11：基于YOLO11的小目标检测模型

IF 2.9 3区工程技术

Digital Signal Processing Pub Date : 2025-06-19 DOI: 10.1016/j.dsp.2025.105411

Xuejian Gong , Jiong Yu , Huayi Zhang , Xinsheng Dong

{"title":"AED-YOLO11: A small object detection model based on YOLO11","authors":"Xuejian Gong , Jiong Yu , Huayi Zhang , Xinsheng Dong","doi":"10.1016/j.dsp.2025.105411","DOIUrl":"10.1016/j.dsp.2025.105411","url":null,"abstract":"<div><div>Small object detection suffers from inherent challenges including noise susceptibility, frequent occlusions, low spatial feature saliency, and imbalanced data distribution. While You Only Look Once 11 (YOLO11) maintains real-time processing capabilities, its detection efficacy on small objects is compromised by insufficient frequency-domain analysis and redundant computational operations in shallow network layers. To overcome these challenges, this study introduces Adaptive Efficient and Dynamic-YOLO11 (AED-YOLO11), a novel detection framework built upon the YOLO11 architecture with specialized enhancements for small object recognition. Specifically, the model introduces the following innovations: First, the Adaptive Frequency Domain Aggregation (AFDA) module dynamically aggregates features using frequency-domain information and channel-wise weighting, resolving frequency inconsistencies in small object images. Second, the Efficient Attention Compression (EAC) module significantly reduces computational costs by compressing channel dimensions and fusing features, thereby improving feature extraction capabilities. Third, the Dynamic Upsampling (DySample) module enhances spatial transformation capabilities through dynamic sampling of input feature maps. Finally, the Wise-IoU(WIoU) loss function is applied to improve detection performance on low-quality samples. Additionally, the detection head structure is optimized to better suit small object detection needs. Collectively, these improvements enhance the model's accuracy and computational efficiency, demonstrating superior performance in complex scenarios. Benchmark tests on VisDrone2019 indicate AED-YOLO11 yields a 4.2% mAP enhancement over baseline approaches while surpassing existing YOLO-series models in small object recognition tasks.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"166 ","pages":"Article 105411"},"PeriodicalIF":2.9,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144329998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Interrupted sampling repeater jamming suppression method based on time-frequency analysis combined with SVM 基于时频分析与支持向量机相结合的中断采样中继器干扰抑制方法

IF 2.9 3区工程技术

Digital Signal Processing Pub Date : 2025-06-19 DOI: 10.1016/j.dsp.2025.105420

Jun Luo , Hui Chen , Weijian Liu , Binbin Li , Xiaoge Wang , Zhaojian Zhang , Haoyang Wang

{"title":"Interrupted sampling repeater jamming suppression method based on time-frequency analysis combined with SVM","authors":"Jun Luo , Hui Chen , Weijian Liu , Binbin Li , Xiaoge Wang , Zhaojian Zhang , Haoyang Wang","doi":"10.1016/j.dsp.2025.105420","DOIUrl":"10.1016/j.dsp.2025.105420","url":null,"abstract":"<div><div>Interrupted sampling repeater jamming (ISRJ) is an intra-pulse coherent jamming, seriously impairing the effectiveness of pulse compression radar. To address this issue, this paper proposes an ISRJ suppression method based on time-frequency analysis combined with support vector machine (SVM), on the basis of the different time-frequency distributions of ISRJ signals and target echo signals after pulse compression. Firstly, the radar received signal is transformed to the time-frequency domain using short-time Fourier transform (STFT) with Gaussian window, improving the resolution of the signal in the time-frequency domain; Secondly, the optimal classification hyperplane is obtained through training the random sample set offline, enabling the intelligent identification and classification of the target and the jamming signal; Then, the Z-score method is applied to eliminate outlier points caused by high jamming sidelobes near the target’s pulse-compressed peaks, further enabling the jamming suppression effectiveness; Finally, Inverse short-time Fourier transform (ISTFT) is performed on the processed time-frequency matrix to reconstruct the target’s pulse-compressed result after jamming suppression. Simulation experiments have validated the high robustness of the proposed method, demonstrating its enhanced jamming suppression performance compared to conventional methods.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"167 ","pages":"Article 105420"},"PeriodicalIF":2.9,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144481416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A real-valued high-resolution coherent DOA estimation method with unknown source number 一种未知源数的实值高分辨率相干DOA估计方法

IF 2.9 3区工程技术

Digital Signal Processing Pub Date : 2025-06-17 DOI: 10.1016/j.dsp.2025.105408

Teng Ma, Minglei Yang, Yu Chen

引用次数: 0

A general MMSE joint detection and estimation of speech signal based on generalized gamma priors 基于广义先验的语音信号的通用MMSE联合检测与估计

IF 2.9 3区工程技术

Digital Signal Processing Pub Date : 2025-06-17 DOI: 10.1016/j.dsp.2025.105405

Siavash Shajari , Mahdi Nangir

{"title":"A general MMSE joint detection and estimation of speech signal based on generalized gamma priors","authors":"Siavash Shajari , Mahdi Nangir","doi":"10.1016/j.dsp.2025.105405","DOIUrl":"10.1016/j.dsp.2025.105405","url":null,"abstract":"<div><div>In this paper, we present a comprehensive model for a simultaneous detection and estimation of Discrete Fourier Transform (DFT) coefficients of speech signals. Our proposed model suggests using a Generalized Gamma Probability Density Function (PDF) to represent the magnitudes of the DFT coefficients of speech signals. Classical probability density functions (PDFs), such as the Rayleigh PDF, are inadequate for accurately modeling speech signal. These models often rely on oversimplified assumptions about the statistical properties of speech signals. These assumptions limit their effectiveness in practical applications. Our study aims to derive a comprehensive simultaneous detection and estimation model based on the Generalized Gamma Distribution (GΓD). We employ the Minimum Mean Square Error (MMSE) estimator to the magnitudes of Discrete Fourier Transform (DFT) coefficients in the Short-Time Fourier Transform (STFT) domain. This approach allows us to effectively model the statistical properties of speech signals using GΓD. Our analyses demonstrate that adopting the GΓD framework can enhance the performance of speech signal detection and estimation in noisy environments, as evidenced by objective evaluation measures.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"167 ","pages":"Article 105405"},"PeriodicalIF":2.9,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144490161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DT-Retinex: low-light enhancement network based on diffuse denoising and light enhancement DT-Retinex：基于漫射去噪和光增强的弱光增强网络

IF 2.9 3区工程技术

Digital Signal Processing Pub Date : 2025-06-17 DOI: 10.1016/j.dsp.2025.105416

Wenjuan Gu , Xin Li , Yuhanke Hu , Junxiang Peng , Xiaobao Liu

{"title":"DT-Retinex: low-light enhancement network based on diffuse denoising and light enhancement","authors":"Wenjuan Gu , Xin Li , Yuhanke Hu , Junxiang Peng , Xiaobao Liu","doi":"10.1016/j.dsp.2025.105416","DOIUrl":"10.1016/j.dsp.2025.105416","url":null,"abstract":"<div><div>Low-light images often suffer from insufficient brightness, blurred details, and noise interference, which degrade visual quality and reduce the accuracy of computer vision tasks. To address these challenges, this paper proposes a low-light image enhancement model named DT-Retinex. The method improves image quality through three stages: image decomposition, reflectance denoising, and illumination enhancement. First, the decomposition network decouples the input image into reflectance and illumination components while preserving structural features. Then, a diffusion model is introduced to progressively denoise the reflectance component, with a customized denoising loss designed to enhance detail restoration. Finally, DT-Retinex adopts an encoder-decoder architecture for illumination enhancement: the encoder extracts multi-level features and leverages the LIT module to model global illumination, while the decoder incorporates CBAM attention to emphasize key regions and adaptively adjust lighting information during spatial reconstruction. Experimental results show that DT-Retinex outperforms existing methods on several benchmark datasets, achieving excellent performance on PSNR, SSIM, and LPIPS, as well as better perceptual naturalness and consistency under no-reference metrics such as NIQE and BRISQUE. Overall, DT-Retinex provides a robust and high-quality solution for low-light image enhancement tasks.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"166 ","pages":"Article 105416"},"PeriodicalIF":2.9,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Real-time instance segmentation algorithm based on mask activation and feature enhancement 基于掩码激活和特征增强的实时实例分割算法

IF 2.9 3区工程技术

Digital Signal Processing Pub Date : 2025-06-16 DOI: 10.1016/j.dsp.2025.105402

Linlin Ma , Jianwei Zhang , Zengyu Cai , Jianxin Ma

{"title":"Real-time instance segmentation algorithm based on mask activation and feature enhancement","authors":"Linlin Ma , Jianwei Zhang , Zengyu Cai , Jianxin Ma","doi":"10.1016/j.dsp.2025.105402","DOIUrl":"10.1016/j.dsp.2025.105402","url":null,"abstract":"<div><div>With the widespread deployment of the Internet of Things, the demand for real-time environmental perception has become increasingly urgent. In this context, instance segmentation technology has emerged as a pixel-level scene perception method, garnering significant attention. This paper proposes a novel and efficient instance segmentation network designed for precise scene perception. In the decoding stage, we design a mask activation module to construct multi-layer weight matrices, with each layer directly activating a mask region of an instance, thereby achieving simplicity and efficiency. During the feature enhancement stage, we introduce two crucial modules to improve performance. Firstly, the global feature perception module models global dependencies through the self-attention mechanism, extending the network's receptive field. Secondly, the foreground feature capture module employs parallel convolutional kernels of various shapes and sizes to comprehensively explore foreground instance information. Experimental verification on the MS-COCO dataset demonstrates that our method achieves a better balance between accuracy and speed, and has potential in practical applications.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"166 ","pages":"Article 105402"},"PeriodicalIF":2.9,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144291281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dual dynamic kernel filtering: Accurate time-frequency representation, reconstruction, and denoising 双动态核滤波：精确时频表示，重建和去噪

IF 2.9 3区工程技术

Digital Signal Processing Pub Date : 2025-06-16 DOI: 10.1016/j.dsp.2025.105407

Skander Bensegueni , Samir Brahim Belhaouari , Yunis Carreon Kahalan

{"title":"Dual dynamic kernel filtering: Accurate time-frequency representation, reconstruction, and denoising","authors":"Skander Bensegueni , Samir Brahim Belhaouari , Yunis Carreon Kahalan","doi":"10.1016/j.dsp.2025.105407","DOIUrl":"10.1016/j.dsp.2025.105407","url":null,"abstract":"<div><div>Time-frequency analysis plays a critical role in characterizing non-stationary signals such as electrocardiograms (ECG), where both spectral and temporal details are paramount. In this study, we introduce Dual Dynamic Kernel Filtering (2DKF) for time-frequency decomposition, emphasizing how kernel selection influences signal representation, reconstruction accuracy, and overall filtering performance. To overcome the limitations associated with signal-dependent single-kernel methods, we propose an innovative Dual hybrid kernel strategy that adaptively integrates multiple kernel functions to capture a wide array of signal characteristics. This approach significantly improves temporal alignment via Dynamic Time Warping (DTW), robustly preserves signal distributions as evidenced by quantile-quantile (QQ) plot analyses, and maintains high frequency fidelity during the filtering process. Extensive experimental comparisons against traditional discrete wavelet transform (DWT) and S-transform filtering, conducted under varying noise conditions, including synthetic noisy ECG with white noise, colored noise (brown and pink), and naturally noisy ECG, demonstrate that our dual hybrid kernel method substantially enhances robustness and consistency in signal reconstruction. Furthermore, we compare our approach with Recursive Multikernel Filtering (RMKF) technique for a benchmark nonlinear signal corrupted by structured noise, alongside wavelet and S-transform techniques. Evaluation metrics, including normalized mean square error (nMSE), root mean square error (RMSE) and correlation coefficients, confirm the superior performance of the proposed approach. These promising results underscore the potential of our method as a powerful tool for the time-frequency analysis of non-stationary signals, with significant implications for advanced ECG signal processing and other biomedical applications.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"166 ","pages":"Article 105407"},"PeriodicalIF":2.9,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144321447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Event-triggered state estimation for networked control systems with silent packet loss and coloured noise 具有无声丢包和彩色噪声的网络控制系统的事件触发状态估计

IF 2.9 3区工程技术

Digital Signal Processing Pub Date : 2025-06-13 DOI: 10.1016/j.dsp.2025.105395

Chang Zhao , Yamin Wang , Ka-Wai Kwok , Xiaoling Liu

引用次数: 0