IEEE open journal of signal processing最新文献_第3页

SINR Analysis of Windowed OFDM in Power Line Communication Systems 电力线通信系统中窗口 OFDM 的 SINR 分析

IF 2.9

IEEE open journal of signal processing Pub Date : 2024-06-26 DOI: 10.1109/OJSP.2024.3419448

Fausto García-Gangoso;Fernando Cruz-Roldán

{"title":"SINR Analysis of Windowed OFDM in Power Line Communication Systems","authors":"Fausto García-Gangoso;Fernando Cruz-Roldán","doi":"10.1109/OJSP.2024.3419448","DOIUrl":"https://doi.org/10.1109/OJSP.2024.3419448","url":null,"abstract":"The use of an accurate cyclic prefix length is crucial in orthogonal frequency division multiplexing (OFDM) to avoid intercarrier and intersymbol interference. Although there have been many works that analyse the interference of windowed OFDM, this study remains open in the context of power line communications (PLCs) taking into account the physical-layer (PHY) specifications of the standards. This paper focuses on obtaining a closed-form expression of the input-output relationship in windowed OFDM power line communication (PLC) systems under the condition of insufficient cyclic prefix, while incorporating various blocks deployed in the PHY under IEEE 1901 standards. The derived analysis is important for quantifying the undesired signal component in each subcarrier at a specific time, which renders the detection of the corresponding symbol more difficult. Moreover, a novel procedure is proposed that allows the use of a smaller number of redundant samples to avoid interference. This novel procedure, performed in the receiver after the windowing stage, replaces the overlap-and-add operations with multiplications, offering the advantage of requiring fewer samples from the time-domain received signal to recover each transmitted data symbol. Numerical results demonstrate the feasibility of interference-free transmission on channels with a larger number of samples, thereby yielding better results across various PLC scenarios.","PeriodicalId":73300,"journal":{"name":"IEEE open journal of signal processing","volume":"5 ","pages":"1052-1060"},"PeriodicalIF":2.9,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10572224","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142518177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Editorial: Special Issue on the ICASSP 2023 Signal Processing Grand Challenges 编辑：ICASSP 2023 信号处理大挑战特刊

IF 2.9

IEEE open journal of signal processing Pub Date : 2024-06-24 DOI: 10.1109/OJSP.2024.3397168

Alexander Bertrand;Ozlem Kalinli

引用次数: 0

Universal Fourier Attack for Time Series 时间序列的通用傅里叶攻击

IF 2.9

IEEE open journal of signal processing Pub Date : 2024-06-14 DOI: 10.1109/OJSP.2024.3402154

Elizabeth Coda;Brad Clymer;Chance DeSmet;Yijing Watkins;Michael Girard

引用次数: 0

Sparse DOA Estimation With Polarimetric Arrays 利用极坐标阵列进行稀疏 DOA 估算

IF 2.9

IEEE open journal of signal processing Pub Date : 2024-06-07 DOI: 10.1109/OJSP.2024.3411468

Augusto Aubry;Marco Boddi;Antonio De Maio;Massimo Rosamilia

引用次数: 0

Multi-Channel Low-Rank Convolution of Jointly Compressed Room Impulse Responses 联合压缩室内脉冲响应的多通道低库卷积

IF 2.9

IEEE open journal of signal processing Pub Date : 2024-06-05 DOI: 10.1109/OJSP.2024.3410089

Martin Jälmby;Filip Elvander;Toon van Waterschoot

{"title":"Multi-Channel Low-Rank Convolution of Jointly Compressed Room Impulse Responses","authors":"Martin Jälmby;Filip Elvander;Toon van Waterschoot","doi":"10.1109/OJSP.2024.3410089","DOIUrl":"https://doi.org/10.1109/OJSP.2024.3410089","url":null,"abstract":"The room impulse response (RIR) describes the response of a room to an acoustic excitation signal and models the acoustic channel between a point source and receiver. RIRs are used in a wide range of applications, e.g., virtual reality. In such an application, the availability of closely spaced RIRs and the capability to achieve low latency are imperative to provide an immersive experience. However, representing a complete acoustic environment using a fine grid of RIRs is prohibitive from a storage point of view and without exploiting spatial proximity, acoustic rendering becomes computationally expensive. We therefore propose two methods for the joint compression of multiple RIRs, based on the generalized low-rank approximation of matrices (GLRAM), for the purpose of efficiently storing RIRs and allowing for low-latency convolution. We show how one of the components of the GLRAM decomposition is virtually invariant to the change of position of the source throughout the room and how this can be exploited in the modeling and convolution. In simulations we show how this offers high compression, with less quality degradation than comparable benchmark methods.","PeriodicalId":73300,"journal":{"name":"IEEE open journal of signal processing","volume":"5 ","pages":"850-857"},"PeriodicalIF":2.9,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10549780","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141543936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SDAT: Sub-Dataset Alternation Training for Improved Image Demosaicing SDAT：用于改进图像去马赛克的子数据集交替训练

IEEE open journal of signal processing Pub Date : 2024-04-30 DOI: 10.1109/OJSP.2024.3395179

Yuval Becker;Raz Z. Nossek;Tomer Peleg

{"title":"SDAT: Sub-Dataset Alternation Training for Improved Image Demosaicing","authors":"Yuval Becker;Raz Z. Nossek;Tomer Peleg","doi":"10.1109/OJSP.2024.3395179","DOIUrl":"https://doi.org/10.1109/OJSP.2024.3395179","url":null,"abstract":"Image demosaicing is an important step in the image processing pipeline for digital cameras. In data centric approaches, such as deep learning, the distribution of the dataset used for training can impose a bias on the networks' outcome. For example, in natural images most patches are smooth, and high-content patches are much rarer. This can lead to a bias in the performance of demosaicing algorithms. Most deep learning approaches address this challenge by utilizing specific losses or designing special network architectures. We propose a novel approach \u0000<bold>SDAT\u0000, Sub-Dataset Alternation Training, that tackles the problem from a training protocol perspective. SDAT is comprised of two essential phases. In the initial phase, we employ a method to create sub-datasets from the entire dataset, each inducing a distinct bias. The subsequent phase involves an alternating training process, which uses the derived sub-datasets in addition to training also on the entire dataset. SDAT can be applied regardless of the chosen architecture as demonstrated by various experiments we conducted for the demosaicing task. The experiments are performed across a range of architecture sizes and types, namely CNNs and transformers. We show improved performance in all cases. We are also able to achieve state-of-the-art results on three highly popular image demosaicing benchmarks.","PeriodicalId":73300,"journal":{"name":"IEEE open journal of signal processing","volume":"5 ","pages":"611-620"},"PeriodicalIF":0.0,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10510581","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140919094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Denoiser-Based Projections for 2D Super-Resolution MRA 基于去噪器的二维超分辨率 MRA 投影

IEEE open journal of signal processing Pub Date : 2024-04-26 DOI: 10.1109/OJSP.2024.3394369

Jonathan Shani;Tom Tirer;Raja Giryes;Tamir Bendory

引用次数: 0

Evaluation of Spectral Estimation Parameters for Direct Sampling FFT-Based Measuring Receivers 评估基于直接采样 FFT 测量接收机的频谱估计参数

IEEE open journal of signal processing Pub Date : 2024-04-16 DOI: 10.1109/OJSP.2024.3389825

Marc García-Bermúdez;Jordi Solé-Lloveras;Martin Hudlička;Marco A. Azpúrua

{"title":"Evaluation of Spectral Estimation Parameters for Direct Sampling FFT-Based Measuring Receivers","authors":"Marc García-Bermúdez;Jordi Solé-Lloveras;Martin Hudlička;Marco A. Azpúrua","doi":"10.1109/OJSP.2024.3389825","DOIUrl":"https://doi.org/10.1109/OJSP.2024.3389825","url":null,"abstract":"The standard CISPR 16-1-1 defines the measuring receiver using a black-box approach and sets requirements for its accuracy and spectral properties. Traditionally, such test receivers were developed using a superheterodyne architecture. Recently, time-domain electromagnetic emission measurement systems have been built employing direct sampling instruments, mainly oscilloscopes, and relying on specific signal processing to emulate the performance of compliant instruments. In these cases, the short-time Fourier transform is used for spectral estimation, but the corresponding electromagnetic compatibility standards lack details for its correct use with respect to parameters such as windowing function, overlapping factor, and frequency interpolation. Moreover, it is unclear which combination of spectral estimation parameters is best fit for this purpose. Obtaining reliable, consistent and low uncertainty spectral estimates of electromagnetic emissions measured in time-domain needs appropriate configuration and tuning of the signal processing algorithms. This paper investigates the error in the calculated spectrum for various reference signals: multitone, chirp pulses and rectangular pulses. The analysis is carried out for each CISPR band from A to D, that is, between 9 kHz and 1 GHz. After \u0000<inline-formula><tex-math>$489.6times 10^{3}$</tex-math></inline-formula>\u0000 iterations, distributed in 1700 different digital implementations of the CISPR 16-1-1 measuring receiver, the simulations outcomes point to certain sets of parameters that showed satisfactory performance overall, being the Nutall, Kaiser, and Parzen windows with more than 75% of overlapping and using interpolation factor higher than 5, generally suitable. Calibration results are used to experimentally verify that a valid set of parameters is adequate to fulfil CISPR 16-1-1 requirements.","PeriodicalId":73300,"journal":{"name":"IEEE open journal of signal processing","volume":"5 ","pages":"588-598"},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10502171","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140818796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sparse Index Tracking: Simultaneous Asset Selection and Capital Allocation via ℓ0 -Constrained Portfolio 稀疏指数跟踪：通过 ℓ0 受限投资组合同时进行资产选择和资本配置

IF 2.9

IEEE open journal of signal processing Pub Date : 2024-04-16 DOI: 10.1109/OJSP.2024.3389810

Eisuke Yamagata;Shunsuke Ono

{"title":"Sparse Index Tracking: Simultaneous Asset Selection and Capital Allocation via ℓ0 -Constrained Portfolio","authors":"Eisuke Yamagata;Shunsuke Ono","doi":"10.1109/OJSP.2024.3389810","DOIUrl":"https://doi.org/10.1109/OJSP.2024.3389810","url":null,"abstract":"Sparse index tracking is a prominent passive portfolio management strategy that constructs a sparse portfolio to track a financial index. A sparse portfolio is preferable to a full portfolio in terms of reducing transaction costs and avoiding illiquid assets. To achieve portfolio sparsity, conventional studies have utilized \u0000<inline-formula><tex-math>$ell _{p}$</tex-math></inline-formula>\u0000-norm regularizations as a continuous surrogate of the \u0000<inline-formula><tex-math>$ell _{0}$</tex-math></inline-formula>\u0000-norm regularization. Although these formulations can construct sparse portfolios, their practical application is challenging due to the intricate and time-consuming process of tuning parameters to define the precise upper limit of assets in the portfolio. In this paper, we propose a new problem formulation of sparse index tracking using an \u0000<inline-formula><tex-math>$ell _{0}$</tex-math></inline-formula>\u0000-norm constraint that enables easy control of the upper bound on the number of assets in the portfolio. Moreover, our approach offers a choice between constraints on portfolio and turnover sparsity, further reducing transaction costs by limiting asset updates at each rebalancing interval. Furthermore, we develop an efficient algorithm for solving this problem based on a primal-dual splitting method. Finally, we illustrate the effectiveness of the proposed method through experiments on the S&P500 and Russell3000 index datasets.","PeriodicalId":73300,"journal":{"name":"IEEE open journal of signal processing","volume":"5 ","pages":"810-819"},"PeriodicalIF":2.9,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10502015","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141447986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MMSFormer: Multimodal Transformer for Material and Semantic Segmentation MMSFormer：用于材料和语义分割的多模态变换器

IEEE open journal of signal processing Pub Date : 2024-04-16 DOI: 10.1109/OJSP.2024.3389812

Md Kaykobad Reza;Ashley Prater-Bennette;M. Salman Asif

{"title":"MMSFormer: Multimodal Transformer for Material and Semantic Segmentation","authors":"Md Kaykobad Reza;Ashley Prater-Bennette;M. Salman Asif","doi":"10.1109/OJSP.2024.3389812","DOIUrl":"https://doi.org/10.1109/OJSP.2024.3389812","url":null,"abstract":"Leveraging information across diverse modalities is known to enhance performance on multimodal segmentation tasks. However, effectively fusing information from different modalities remains challenging due to the unique characteristics of each modality. In this paper, we propose a novel fusion strategy that can effectively fuse information from different modality combinations. We also propose a new model named \u0000<underline>M\u0000ulti-\u0000<underline>M\u0000odal \u0000<underline>S\u0000egmentation Trans\u0000<underline>Former\u0000 (MMSFormer) that incorporates the proposed fusion strategy to perform multimodal material and semantic segmentation tasks. MMSFormer outperforms current state-of-the-art models on three different datasets. As we begin with only one input modality, performance improves progressively as additional modalities are incorporated, showcasing the effectiveness of the fusion block in combining useful information from diverse input modalities. Ablation studies show that different modules in the fusion block are crucial for overall model performance. Furthermore, our ablation studies also highlight the capacity of different input modalities to improve performance in the identification of different types of materials.","PeriodicalId":73300,"journal":{"name":"IEEE open journal of signal processing","volume":"5 ","pages":"599-610"},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10502124","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140822028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0