Baoxin Su, Shufeng Li, Junwei Zhang, Evgeny Belyaev
{"title":"A Non-Binary Dual Cascade Polar Codes Construction and Low-Complexity SCL Decoding","authors":"Baoxin Su, Shufeng Li, Junwei Zhang, Evgeny Belyaev","doi":"10.1049/ell2.70306","DOIUrl":"https://doi.org/10.1049/ell2.70306","url":null,"abstract":"<p>This paper is dedicated to error-correction coding using polar codes. First, we design an error-correction approach including two cascade non-binary polar coding (NB-CPolar) structures and a cyclic redundancy check (CRC) code. Second, we propose a low-complexity decoding algorithm based on non-binary successive cancellation list (NB-LSCL) decoding. In order to improve the correction performance, during the level-2 NB-Polar decoding process, we propose to prioritize the CRC decision, retaining the paths with higher reliability, before performing the level-1 NB-Polar decoding operation. Simulation results demonstrate that compared with the baseline scheme, the NB-CPolar encoder and NB-LSCL decoding algorithm significantly improve the error correction performance.</p>","PeriodicalId":11556,"journal":{"name":"Electronics Letters","volume":"61 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2025-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ell2.70306","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144135646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Slow-Scale Instability in the Two-Phase Interleaved Fractional-Order Boost DC–DC Converter: Analysis and Confirmation","authors":"Chunling Hao, Faqiang Wang, Hao Qiu","doi":"10.1049/ell2.70291","DOIUrl":"https://doi.org/10.1049/ell2.70291","url":null,"abstract":"<p>A steady-state analytic approach based on the equivalent small parameter method (ESPM) is proposed for fractional-order systems in which the state variables have non-consistent periods. This approach is systematically employed to formulate a mathematical model for a two-phase interleaved parallel fractional-order boost DC–DC converter, considering parasitic effects. Through rigorous theoretical analysis, the underlying mechanism governing slow-scale instabilities in such systems is fundamentally elucidated. The effectiveness of the proposed method and theoretical analysis is verified by means of simulations and experiments, showing that the theoretical prediction is basically consistent with the observed results.</p>","PeriodicalId":11556,"journal":{"name":"Electronics Letters","volume":"61 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ell2.70291","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144118204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Seonmin Cho, Soyoon Park, Youngjae Choi, Seungeui Lee, Youngseok Bae, Seongwook Lee
{"title":"Joint Noise Suppression and Resolution Enhancement of ISAR Images Using Integrated Neural Networks","authors":"Seonmin Cho, Soyoon Park, Youngjae Choi, Seungeui Lee, Youngseok Bae, Seongwook Lee","doi":"10.1049/ell2.70303","DOIUrl":"https://doi.org/10.1049/ell2.70303","url":null,"abstract":"<p>This paper proposes an integrated neural network for joint noise suppression and resolution enhancement of inverse synthetic aperture radar (ISAR) images. Unlike conventional methods that address both challenges separately, we present a unified framework that can address them simultaneously. To achieve this, we first generate a comprehensive dataset of ISAR images for various targets under different conditions using a simulation-based method. Subsequently, we develop separate generative models for noise suppression and resolution enhancement, which are then combined sequentially. This combined network uses a joint optimization strategy in training process, simultaneously updating the weights of the two networks. The proposed integrated network achieved an average peak signal-to-noise ratio and structural similarity index measure of 34.69 dB and 0.95, respectively. It demonstrates that the proposed network effectively achieves both noise suppression and resolution enhancement within a single network.</p>","PeriodicalId":11556,"journal":{"name":"Electronics Letters","volume":"61 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ell2.70303","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144126020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimized Design of \u0000 \u0000 \u0000 Σ\u0000 Δ\u0000 \u0000 $Sigma Delta$\u0000 Modulators Using Deep-Learning and Simulated Annealing","authors":"Gustavo Liñán-Cembrano, José M. de la Rosa","doi":"10.1049/ell2.70256","DOIUrl":"https://doi.org/10.1049/ell2.70256","url":null,"abstract":"<p>This letter presents a MATLAB toolbox for the automated high-level design and optimization of analogue-to-digital converters (ADCs), using sigma-delta modulators (<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>Σ</mi>\u0000 <mi>Δ</mi>\u0000 <mi>Ms</mi>\u0000 </mrow>\u0000 <annotation>$Sigma Delta{rm Ms}$</annotation>\u0000 </semantics></math>) as case studies. The tool combines machine learning (ML) techniques and behavioural simulation to obtain the optimum set of building-block (amplifiers, comparators, etc.) requirements for a given set of specifications, namely resolution, signal bandwidth and power consumption. Two machine learning blocksgradient boosting classifiers and regression-type artificial neural networks—are trained, using Python libraries, to identify the best ADC architecture as well as to infer a set of design parameters which yields ADC specifications. The result from the ML blocks can be cross-checked in behavioural simulations in MATLAB and also optimized with respect to signal-to-noise ratio (SNR), power consumption, or figure-of-merit (FoM) using an embedded simulated annealing (SA) process. The toolbox is controlled through a graphical user interface (GUI) for MATLAB which guides the designer through the whole process, from specifications to obtaining an implementation that meets the required specifications.</p>","PeriodicalId":11556,"journal":{"name":"Electronics Letters","volume":"61 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ell2.70256","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144126021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}