Digital Signal Processing最新文献

{"title":"Automatic modulation recognition based on sample-transferable and branch-scalable method for signals in complex multipath channel","authors":"Yitong Lu,&nbsp;Shujuan Hou,&nbsp;Shiyi Yuan,&nbsp;Qin Zhang,&nbsp;Yazhe He,&nbsp;Shouzhi Wang","doi":"10.1016/j.dsp.2025.105406","DOIUrl":"10.1016/j.dsp.2025.105406","url":null,"abstract":"<div><div>At present, there are a large number of mature deep learning related studies on automatic modulation recognition (AMR) for signals in the additive white Gaussian noise (AWGN) or fixed multipath channel. However, in actual communication environments, the AMR method is required to have strong generalization ability due to the complexity and variability of multipath channels. Thus, we propose a sample-transferable and branch-scalable method suitable for signals in different multipath channels. According to the generation principle of multipath signals, we first estimate the multipath signals based on the direction of arrival (DOA) estimation algorithm to obtain characteristic parameters such as the number of paths and the direction of arrival. Then we decompose the multipath signals into multi-branch single-path signals using the estimation results. On this basis, we propose a multi-branch neural network trained with signals in the AWGN channel, with the decomposed multi-branch single-path signals serving as inputs. Hence, sample transfer from the training signals in the AWGN channel to the test signals in the multipath channel can be realized, significantly improving the generalization ability of the network. Moreover, we introduce the attention mechanism module to perform feature-level fusion on multi-branch signals, and use multipath signals to obtain additional recognition gain compared to single-path signals. In response to the uncertainty of multipath number in complex multipath channel environments, we propose a branch-scalable dynamic neural network (BSDNN) with novel “dual-branch training, multi-branch recognition”, and realize the recognition of multipath signals with arbitrary path number using the network structure trained with dual-branch signals. The experimental results show that our proposed BSDNN trained with the dual-branch signals in the AWGN channel can successfully transfer to modulation recognition of multipath signals with any number of paths. Furthermore, the method exhibits advantages in terms of lightweight design, with fewer network parameters and training time.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"166 ","pages":"Article 105406"},"PeriodicalIF":2.9,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144312884","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}

{"title":"Design of linear-phase IIR integrators with maximally-flat and Chebyshev magnitude responses","authors":"Ivan Krstić ,&nbsp;Goran Stančić ,&nbsp;Jasna Radulović","doi":"10.1016/j.dsp.2025.105400","DOIUrl":"10.1016/j.dsp.2025.105400","url":null,"abstract":"<div><div>This paper proposes two methods for designing linear-phase infinite impulse response integrators. The first method, referred to as the maximally-flat one, imposes flatness conditions on the frequency response error function, leading to a system of linear equations that have to be solved to determine unknown coefficients. Furthermore, a relation is established between the proposed maximally-flat integrators and existing integer-order linear-phase integrators derived using the algebraic polynomial-based quadrature rules, demonstrating that the latter represent special cases of the proposed integrators. The second method, referred to as the optimal one, minimizes the complex frequency response error function in the weighted Chebyshev sense, which is achieved by an efficient exchange algorithm that exhibits rapid convergence. The proposed linear-phase integrators are also compared with several existing linear- and nearly linear-phase integrators.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"166 ","pages":"Article 105400"},"PeriodicalIF":2.9,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144280801","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}

{"title":"Minimization of pseudo fountain penalty for sparse signal recovery","authors":"Zhihua Li ,&nbsp;Feixiang Zhang ,&nbsp;Ning Yu","doi":"10.1016/j.dsp.2025.105404","DOIUrl":"10.1016/j.dsp.2025.105404","url":null,"abstract":"<div><div>In this paper, we propose a novel Pseudo-fountain (PF) penalty that builds upon and extends compressed sensing (CS) theory. The PF penalty optimizes dual parameters in coordination, enhancing its adaptability to the sparsity of signals. Meanwhile, leveraging the renowned RIP theory, we establish explicit conditions for the exact and robust recovery of signals. Additionally, we develop a Difference of Convex Algorithm-PF (DCA-PF) tailored for the constrained sparse signal recovery model formulated in this work. The experimental results demonstrate that the PF penalty outperforms its counterparts in terms of robustness, stability, and sparsity for sparse signal recovery.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"166 ","pages":"Article 105404"},"PeriodicalIF":2.9,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144297769","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}

{"title":"A novel stochastic model for the steady-state performance of norm-penalized adaptive algorithms","authors":"Lucas P.R. da Silva ,&nbsp;Fabio A.A. Andrade ,&nbsp;Milena F. Pinto ,&nbsp;Gilson A. Giraldi ,&nbsp;Diego Barreto Haddad","doi":"10.1016/j.dsp.2025.105403","DOIUrl":"10.1016/j.dsp.2025.105403","url":null,"abstract":"<div><div>This paper proposes a new model to estimate the asymptotic performance of adaptive algorithms with norm penalization of the adaptive coefficient vector. The attraction-to-zero term is modeled as a piecewise linear function, allowing the proposed approach to approximate, with arbitrary precision, the behavior of multiple algorithms from the literature. Assuming a white input signal, it is possible to derive a general model capable of predicting the algorithm's asymptotic performance in terms of mean square deviation. The closed-form expression obtained for the mean square deviation is then approximated using heuristics, allowing the optimal value of the parameter regulating the norm penalization to also be determined through a closed-form formula. The derived formulas were extensively tested and validated through simulations, demonstrating good accuracy, with a maximum error of 0.17 dB between the theoretical and simulated values.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"166 ","pages":"Article 105403"},"PeriodicalIF":2.9,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144297768","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}

{"title":"Human gait recognition using dense residual network and hybrid attention technique with back-flow mechanism","authors":"Mohammad Iman Junaid,&nbsp;Sandeep Madarapu,&nbsp;Samit Ari","doi":"10.1016/j.dsp.2025.105401","DOIUrl":"10.1016/j.dsp.2025.105401","url":null,"abstract":"<div><div>Gait recognition is a promising biometric technique for person identification, either as a standalone method or in combination with other modalities. A major challenge lies in extracting robust gait features from silhouettes that remain invariant to variation in clothing, carried objects, and camera viewpoints. Recent advances using attention-based convolutional neural networks (CNNs) have improved gait recognition performance; however, many existing methods struggle to preserve semantic information across network layers due to information loss during the stages of downsampling. To address this issue, a novel residual dense back-flow attention network (RDBA-Net) is proposed, which integrates dual-branch hybrid self-attention network (DHSAN) modules with densely connected residual dense blocks (RDBs), and the output features are concatenated in a back-flow direction. This design enables effective learning of discriminative gait features by leveraging attention cues at both spatial-level and temporal-level from silhouette sequences. Furthermore, back-flow mechanism enhances feature learning in earlier layers by reusing refined semantic information from deeper layers. Experimental evaluations on two benchmark datasets, CASIA B and OU-MVLP, demonstrate that RDBA-Net, achieves notable improvements in accuracy compared to existing state-of-the-art methods, with gains up to 91.6% on CASIA B and 89.2% on OU-MVLP under challenging conditions.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"166 ","pages":"Article 105401"},"PeriodicalIF":2.9,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144307331","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}

{"title":"PMDFN3D: Pre-mid dual fusion network for 3D object detection","authors":"Haishun Du ,&nbsp;Sen Wang ,&nbsp;Wenzhe Zhang ,&nbsp;Linbing Cao","doi":"10.1016/j.dsp.2025.105399","DOIUrl":"10.1016/j.dsp.2025.105399","url":null,"abstract":"<div><div>In recent years, multi-modality 3D object detection technology is gradually becoming the mainstream of 3D object detection. In multi-modality 3D object detection, effectively fusing information from point cloud data and image data remains a significant challenge. Existing multi-modality 3D object detection models mainly use one of the pre-, mid- or post-fusion strategies to fuse image data and point cloud data, and each of these fusion strategies has some shortcomings. Currently, integrating multiple fusion strategies into a framework is still a research gap in the field of multi-modality 3D object detection. To fill this gap, we propose a pre-mid dual fusion network for 3D object detection (PMDFN3D), which skillfully integrates the pre-fusion and mid-fusion into a unified framework. Specifically, we first design a depth-guided cross-modality feature fusion module that enables the effective integration of image and point features without requiring complex feature alignment operations. Then, we design a neighboring feature interaction attention module to mitigate the impact of down-sampling operations in the point cloud backbone network on the precision of point features. Finally, we design a simple object-level feature selector and an object-level feature-guided cross-modality feature fusion module, which adaptively integrate image features relevant to the objects with object-level point features. Experimental results on the SUN RGB-D dataset demonstrate that our network has achieved state-of-the-art performance in 3D object detection.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"166 ","pages":"Article 105399"},"PeriodicalIF":2.9,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144263122","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}

{"title":"A high-reliability dual-mode M-ary differential chaos shift keying system with index modulation","authors":"Gang Zhang ,&nbsp;Yongqi Guo ,&nbsp;Xinyu Xiong","doi":"10.1016/j.dsp.2025.105388","DOIUrl":"10.1016/j.dsp.2025.105388","url":null,"abstract":"<div><div>This paper introduces a novel high-efficiency dual-mode multi-carrier differential chaos shift keying (HRDM-MDCSK-IM) system that integrates index modulation and noise suppression techniques. The system utilizes distinct modulation schemes for active and inactive time slots on each subcarrier and encodes them using reference selection indexing and combined Walsh code indexing, thereby enhancing the system's efficiency. At the receiver's end, the system employs the sliding average of reference signals to reduce noise and performs secondary noise reduction on information signals during active time slots to recover information bits. This approach optimizes the bit error rate (BER) performance and improves the overall system performance. Simulation results demonstrate that the HRDM-MDCSK-IM system significantly outperforms existing benchmark systems in terms of data rates and spectral efficiency. The paper also derives the theoretical expressions for the BER of the system under both additive white Gaussian noise (AWGN) and multipath Rayleigh fading channels, and verifies their accuracy through simulation. The theoretical analysis, coupled with simulation results, confirms the superior performance of the HRDM-MDCSK-IM system and highlights its potential for practical applications in high-efficiency wireless communication systems.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"166 ","pages":"Article 105388"},"PeriodicalIF":2.9,"publicationDate":"2025-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144297767","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}

{"title":"VOLEMIA: Non-invasive blood pressure estimation using temporal-spectral convolutional network","authors":"Trishna Saikia ,&nbsp;Satwik Vankayalapati ,&nbsp;Puneet Gupta ,&nbsp;Pasi Liljeberg","doi":"10.1016/j.dsp.2025.105393","DOIUrl":"10.1016/j.dsp.2025.105393","url":null,"abstract":"<div><div>This paper introduces a novel method, <em>VOLEMIA</em>, to improve blood pressure (BP) estimation from the photoplethysmography (PPG) signal. Existing literature has often relied on long-duration PPG signals, which can be noise-prone, thereby compromising the performance of BP estimation. As a solution, <em>VOLEMIA</em> presents the PulseBlend Deconstructor (PBD), which partitions the lengthy PPG signal into shorter segments and consolidates the segments to extract the noise-resilient PPG signal. Furthermore, <em>VOLEMIA</em> presents the Pulse Spectra Extractor (PSA) mechanism to extract pulsatile spectral features from the PPG signal because spectral features provide relevant cues for systolic BP (SBP) and diastolic BP (DBP). Unlike existing methods, <em>VOLEMIA</em> incorporates these features into an advanced sequential deep learning framework while also considering the correlation between SBP and DBP. A new composite loss function is proposed to enable the network to learn both individual and correlated BP features, enhancing performance. Experimental results on our newly designed DILPPG and publicly available MIMIC-II dataset demonstrate that <em>VOLEMIA</em> exhibits superior performance than the existing methods across both datasets. Also, it indicates that key components of <em>VOLEMIA</em>, like PBD, PSA, and composite loss function, play a crucial role in performance improvement. Dataset link: <span><span>https://github.com/TrishnaSaikia/-DILPPG-Dataset.git</span><svg><path></path></svg></span></div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"166 ","pages":"Article 105393"},"PeriodicalIF":2.9,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144254332","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}

{"title":"Online spatial alignment and fusion for networked radars on moving platforms only using target position information","authors":"Chenyu Zhu,&nbsp;Xiaoyu Cong,&nbsp;Yubing Han,&nbsp;Weixing Sheng","doi":"10.1016/j.dsp.2025.105375","DOIUrl":"10.1016/j.dsp.2025.105375","url":null,"abstract":"<div><div>Spatial alignment is a prerequisite for cooperative detection in networked radars, even minor biases in spatial alignment can result in large errors in the converted target geolocation. Existing spatial alignment algorithms commonly rely on the Global Positioning System (GPS) and Inertial Measurement Unit (IMU) to provide positional data and attitude angles. To overcome this limitation, we formulate the spatial alignment relationships between radars as an optimization function based on a sliding window mechanism. This function is then solved recursively using a combination of Tikhonov regularization and recursive least squares (RLS) to obtain accurate spatial alignment estimates. To provide criteria for the selection of reference radars before multi-radar alignment, a dynamic preselection strategy is put forward. This strategy creates a prior advantage for parameter estimation by analyzing the correlations between target trajectories from different radars. Considering the coupling between alignment and fusion processes, we present a feedback adjustment method to further improve the accuracy of alignment and fusion. Simulation results show the effectiveness of the proposed algorithm and its superior performance compared with traditional algorithms under the same conditions.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"166 ","pages":"Article 105375"},"PeriodicalIF":2.9,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144241641","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}

{"title":"Statistical CSI-based dual-hop hybrid RIS-assisted wireless communication","authors":"Shuang Liang,&nbsp;Guangliang Ren","doi":"10.1016/j.dsp.2025.105398","DOIUrl":"10.1016/j.dsp.2025.105398","url":null,"abstract":"<div><div>Statistical channel state information (S-CSI) based ergodic achievable rate maximization is investigated for dual-hop hybrid reconfigurable intelligent surfaces (D-HRIS) assisted single-user wireless communication systems. A communication model, in which the transmitted signal is reflected through passive RIS (pRIS) to the active RIS (aRIS) and then reflected to the receiver via aRIS, is regarded as D-HRIS-assisted communication. The ergodic achievable rate is analyzed and its approximate expression is derived for this system. Based on the S-CSI, a low-complexity iterative updating scheme is proposed to design the precoding of the base station (BS) and the reflecting matrices of hybrid RISs (HRIS) to maximize the ergodic achievable rate. Specifically, the ergodic achievable rates of the proposal are 1.32 and 1.16 times larger than those of the dual-hop pRIS-aided scheme when the number of elements at the second-hop RIS is 20 and 100, respectively. When the Rician-K factor is larger than 0 dB, the ergodic achievable rate of the proposal is close to that of the instantaneous channel state information (I-CSI) based D-HRIS-assisted communication. And the performance of the system can still be guaranteed when RIS employs discrete phase shifters.</div></div>","PeriodicalId":51011,"journal":{"name":"Digital Signal Processing","volume":"166 ","pages":"Article 105398"},"PeriodicalIF":2.9,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144241642","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}