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CS-FSCL decoding algorithm of polar codes based on critical sets

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Optoelectronics Letters 2024年第7期20卷 418-423页

作者： YUAN Jianguo ZHANG Fengguo HE Jingjie PANG Yu school of Optoelectronic engineering Chongqing University of Posts and Telecommunications

In order to reduce the number of redundant candidate codewords generated by the fast successive cancellation list(FSCL) decoding algorithm for polar codes, a simplified FSCL decoding algorithm based on critical sets(CS-FSCL) of polar codes is proposed. The algorithm utilizes the number of information bits belonging to the CS in the special nodes, such as Rate-1 node, repetition(REP) node and single-parity-check(SPC) node, to constrain the number of the path splitting and avoid the generation of unnecessary candidate codewords, and thus the latency and computational complexity are reduced. Besides, the algorithm only flips the bits corresponding to the smaller log-likelihood ratio(LLR) values to generate the sub-maximum likelihood(sub-ML) decoding codewords and ensure the decoding performance. Simulation results show that for polar codes with the code length of 1 024, the code rates of 1/4, 1/2 and 3/4, the proposed CS-FSCL algorithm, compared with the conventional FSCL decoding algorithm, can achieve the same decoding performance, but reduce the latency and computational complexity at different list sizes. Specifically, under the list size of L=8, the code rates of R=1/2 and R=1/4, the latency is reduced by 33% and 13% and the computational complexity is reduced by 55% and 50%, respectively.

关键词： A

Improved Twin Support Vector Machine Algorithm and Applications in Classification Problems

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China Communications 2024年第5期21卷 261-279页

作者： Sun Yi Wang Zhouyang Beijing University of Posts and telecommunications School of Computer Science(National Pilot Software Engineering School) Beijing University of Posts and telecommunications International School

The distribution of data has a significant impact on the results of classification.When the distribution of one class is insignificant compared to the distribution of another class,data imbalance occurs.This will result in rising outlier values and noise.Therefore,the speed and performance of classification could be greatly affected.Given the above problems,this paper starts with the motivation and mathematical representing of classification,puts forward a new classification method based on the relationship between different classification formulations.Combined with the vector characteristics of the actual problem and the choice of matrix characteristics,we firstly analyze the orderly regression to introduce slack variables to solve the constraint problem of the lone point.Then we introduce the fuzzy factors to solve the problem of the gap between the isolated points on the basis of the support vector machine.We introduce the cost control to solve the problem of sample skew.Finally,based on the bi-boundary support vector machine,a twostep weight setting twin classifier is constructed.This can help to identify multitasks with feature-selected patterns without the need for additional optimizers,which solves the problem of large-scale classification that can’t deal effectively with the very low category distribution gap.

关键词： fuzzy ordered regression(OR) relaxing variables twin support vector machine

Learning background restoration and local sparse dictionary for infrared small target detection

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Optoelectronics Letters 2024年第7期20卷 437-448页

作者： HE Yue ZHANG Rui XI Chunmei ZHU Hu school of Communications and Information engineering Nanjing University of Posts and Telecommunications

This paper proposes a method for learning background restoration for infrared small target detection, employing a local sparse dictionary alongside an equalized structural texture representation. The method is specifically designed for the detection of small infrared targets, accommodating various levels of brightness, spatial size, and intensity. Our proposed model intelligently combines global low-rankness and local sparsity to estimate the rank of the background tensor, leveraging spatial and structural information to overcome the limitations posed by insufficient detailed texture knowledge. Subsequently, a structural texture representation, combining local gradient maps and local intensity maps, is applied to emphasize small objects. By comparing our method with nine advanced and representative approaches and quantifying the comparison using various metrics, the experimental results indicate that our proposed method has achieved favorable outcomes in both quantitative assessments and visual results.

关键词： A

Research on human gait sensing based on triboelectric nanogenerator

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Nanotechnology and Precision engineering 2024年第2期7卷 32-40页

作者： Gang Yang Lifang Wang Jiayun Tian school of Communication and Information engineering Xi’an University of Posts and TelecommunicationsXi’an 710121China

To address the problem of frequent battery replacement for wearable sensors applied to fall detection among the elderly,a portable and lowcost triboelectric nanogenerator(TENG)-based self-powered sensor for human gait monitoring is proposed.The main fabrication materials of the TENG are polytetrafluoroethylene(PTFE)film,aluminum(Al)foil,and polyimide(PI)film,where PTFE and Al are the friction layer materials and the PI film is used to improve the output performance.Exploiting the ability of TENGs to monitor changes in environmental conditions,a self-powered sensor based on the TENG is placed in an insole to collect gait information.Since a TENG does not require a power source to convert physical and mechanical signals into electrical signals,the electrical signals can be used as sensing signals to be analyzed by a computer to recognize daily human activities and fall status.Experimental results show that the accuracy of the TENG-based sensor for recognizing human gait is 97.2%,demonstrating superior sensing performance and providing valuable insights for future monitoring of fall events in the elderly population.

关键词： Triboelectric nanogenerator Sensor Gait monitoring

FSCIL-EACA: Few-Shot Class-Incremental Learning Network Based on Embedding Augmentation and Classifier Adaptation for Image Classification

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Chinese Journal of Electronics 2024年第1期33卷 139-152页

作者： Ruru ZHANG Haihong E Meina SONG school of Computer Science Beijing University of Posts and Telecommunications Education Department Information Network engineering Research Center Beijing University of Posts and Telecommunications

The ability to learn incrementally is critical to the long-term operation of AI systems. Benefiting from the power of few-shot class-incremental learning(FSCIL), deep learning models can continuously recognize new classes with only a few samples. The difficulty is that limited instances of new classes will lead to overfitting and exacerbate the catastrophic forgetting of the old classes. Most previous works alleviate the above problems by imposing strong constraints on the model structure or parameters, but ignoring embedding network transferability and classifier adaptation(CA), failing to guarantee the efficient utilization of visual features and establishing relationships between old and new classes. In this paper, we propose a simple and novel approach from two perspectives: embedding bias and classifier bias. The method learns an embedding augmented(EA) network with cross-class transfer and class-specific discriminative abilities based on self-supervised learning and modulated attention to alleviate embedding bias. Based on the adaptive incremental classifier learning scheme to realize incremental learning capability,guiding the adaptive update of prototypes and feature embeddings to alleviate classifier bias. We conduct extensive experiments on two popular natural image datasets and two medical datasets. The experiments show that our method is significantly better than the baseline and achieves state-of-the-art results.

关键词： Few-shot class-incremental learning Embedding augmentation Classifier adaptation Image classification

Design of tightly linked dual ring antenna and imaging of magnetic field distribution using a diamond fiber probe

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Chinese Physics B 2024年第2期33卷 347-352页

作者：叶青云薛雅文何飞越赵旭彤卞雨辰卢文韬王金旭陈鸿浩夏圣开曾明菁杜关祥 College of telecommunications and Information engineering Nanjing University of Posts and TelecommunicationsNanjing 210003China College of Science Nanjing University of Posts and TelecommunicationsNanjing 210003China school of Computer Science Nanjing University of Posts and TelecommunicationsNanjing 210023China Bell Honors school Nanjing University of Posts and TelecommunicationsNanjing 210023China

A tightly linked dual ring antenna is designed,and it is specifically tailored for uniformly coupling the microwave magnetic field to the nitrogen-vacancy(NV)center.The designed antenna operates at a center frequency of about 2.87 GHz,with a bandwidth of around 200 MHz,allowing it to address multiple resonance peaks in the optically detected magnetic resonance(ODMR)spectrum in an external magnetic field.Moreover,the antenna generates a fairly uniform magnetic field in a range with a radius of 0.75 mm.High resolution imaging of the magnetic field distribution on the surface of the antenna is conducted by using a fiber diamond probe.We also investigate the effect of magnetic field uniformity on the linewidth of ODMR,so as to provide insights into reducing the inhomogeneous broadening of ODMR.

关键词： nitrogen vacancy(NV) microwave(MW)imaging inhomogeneous broadening

High-resolution imaging of magnetic fields of banknote anti-counterfeiting strip using fiber diamond probe

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Chinese Physics B 2024年第4期33卷 720-727页

作者：赵旭彤何飞越薛雅文马文豪殷筱晗夏圣开曾明菁杜关祥 College of telecommunications and Information engineering Nanjing University of Posts and TelecommunicationsNanjing 210003China College of Science Nanjing University of Posts and TelecommunicationsNanjing 210003China school of Computer Science Nanjing University of Posts and TelecommunicationsNanjing 210023China Bell Honors school Nanjing University of Posts and TelecommunicationsNanjing 210023China

Counterfeiting of modern banknotes poses a significant challenge,prompting the use of various preventive measures.One such measure is the magnetic anti-counterfeiting strip.However,due to its inherent weak magnetic properties,visualizing its magnetic distribution has been a longstanding challenge.In this work,we introduce an innovative method by using a fiber optic diamond probe,a highly sensitive quantum sensor designed specifically for detecting extremely weak magnetic fields.We employ this probe to achieve high-resolution imaging of the magnetic fields associated with the RMB 50denomination anti-counterfeiting strip.Additionally,we conduct computer simulations by using COMSOL Multiphysics software to deduce the potential geometric characteristics and material composition of the magnetic region within the anti-counterfeiting strip.The findings and method presented in this study hold broader significance,extending the RMB 50 denomination to various denominations of the Chinese currency and other items that employ magnetic anti-counterfeiting strips.These advances have the potential to significantly improve and promote security measures in order to prevent the banknotes from being counterfeited.

关键词： banknote anti-counterfeiting strip nitrogen-vacancy(NV)centers magnetic field imaging numerical simulation

FlowGANAnomaly: Flow-Based Anomaly Network Intrusion Detection with Adversarial Learning

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Chinese Journal of Electronics 2024年第1期33卷 58-71页

作者： Zeyi LI Pan WANG Zixuan WANG school of Computer Science Nanjing University of Posts and Telecommunications school of Modern Posts Nanjing University of Posts and Telecommunications school of Internet of Things Nanjing University of Posts and Telecommunications

In recent years, low recall rates and high dependencies on data labelling have become the biggest obstacle to developing deep anomaly detection(DAD) techniques. Inspired by the success of generative adversarial networks(GANs) in detecting anomalies in computer vision and imaging, we propose an anomaly detection model called Flow GANAnomaly for detecting anomalous traffic in network intrusion detection systems(NIDS). Unlike traditional GAN-based approaches, which are composed of a flow encoder, a convolutional encoder-decoder-encoder, a flow decoder and a convolutional encoder, the architecture of this model consists of a generator(G) and a discriminator(D).Flow GANAnomaly maps the different types of traffic feature data from separate datasets to a uniform feature space,thus can capture the normality of network traffic data more accurately in an adversarial manner to mitigate the problem of the high dependence on data labeling. Moreover, instead of simply detecting the anomalies by the output of D, we proposed a new anomaly scoring method that integrates the deviation between the output of two Gs’ convolutional encoders with the output of D as weighted scores to improve the low recall rate of anomaly detection. We conducted several experiments comparing existing machine learning algorithms and existing deep learning methods(Auto Encoder and VAE) on four public datasets(NSL-KDD, CIC-IDS2017, CIC-DDo S2019, and UNSW-NB15). The evaluation results show that Flow GANAnomaly can significantly improve the performance of anomaly-based NIDS.

关键词： Anomaly detection Unsupervised learning Generative adversarial network Intrusion detection system

An improved construction algorithm of polar codes based on the frozen bits

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Optoelectronics Letters 2024年第3期20卷 157-162页

作者： YUAN Jianguo ZHANG Fengguo YU Linfeng PANG Yu school of Optoelectronic engineering Chongqing University of Posts and TelecommunicationsChongqing 400065China

In order to improve the problems that the minimum hamming weight(MHW) of the polar codes of the traditional Gaussian approximation(GA) construction is small and its performance is not good enough, an improved channel construction algorithm of polar codes based on frozen bits is proposed by combining the construction of the Reed-Muller(RM) code to effectively increase the MHW and analyzing the correcting and checking functions of the frozen bits in the successive cancellation list(SCL) decoding.

关键词： polar algorithm successive