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Proceedings of the 2020 4th International Conference on Digital Signal Processing最新文献

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Automatic Matching of White Matter Hyperintensity Lesions in Longitudinal Brain Magnetic Resonance Imaging 脑纵向磁共振成像中白质高强度病变的自动匹配
Proceedings of the 2020 4th International Conference on Digital Signal Processing Pub Date : 2020-06-19 DOI: 10.1145/3408127.3408129
Chih-Ying Gwo
{"title":"Automatic Matching of White Matter Hyperintensity Lesions in Longitudinal Brain Magnetic Resonance Imaging","authors":"Chih-Ying Gwo","doi":"10.1145/3408127.3408129","DOIUrl":"https://doi.org/10.1145/3408127.3408129","url":null,"abstract":"Compared with elderly people with normal cognition, Alzheimer's disease (AD) type dementia patients have more extensive white matter hyperintensities (WMH) lesions, suggesting their role in the pathogenesis of dementia and neurocognitive dysfunction. In the process of the analysis, lesion markers and matches were primarily assessed by experts, which was time-consuming and limited the analysis of WMH or related symptoms for large number of whole brain images. In this study, we proposed a systematic procedure based on high order Zernike transform to align the images of one subject at different scan times. To estimate the rotation angle between the aligned images, we extract the keypoints and their corresponding features from the images based on Scale-Invariant Feature Transform (SIFT) to. Then, the matching white matter hyperintensities in the pre and post stages is performed after all the post images are rotated and translated to the coordinates of the first scan image.","PeriodicalId":383401,"journal":{"name":"Proceedings of the 2020 4th International Conference on Digital Signal Processing","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126808310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Self-Interference Cancellation in Radar Jammer Based on Deep Neural Networks 基于深度神经网络的雷达干扰机自干扰消除
Proceedings of the 2020 4th International Conference on Digital Signal Processing Pub Date : 2020-06-19 DOI: 10.1145/3408127.3408188
Xiaoyu Li, Xihang Yin, Xin Yao
{"title":"Self-Interference Cancellation in Radar Jammer Based on Deep Neural Networks","authors":"Xiaoyu Li, Xihang Yin, Xin Yao","doi":"10.1145/3408127.3408188","DOIUrl":"https://doi.org/10.1145/3408127.3408188","url":null,"abstract":"In the radar electronic warfare, the problem in the transmitter-receiver isolation of the radar jammer will affect the detection and reception of the jammer itself seriously. Adaptive algorithms are often used to solve the problem. The weights of the filter in the algorithms are updated according to the minimum mean square error when it works. This method cannot effectively eliminate the nonlinear components of the self-interference signal in some special cases. In order to solve this problem, a method of self - interference cancellation based on deep neural networks is proposed in this paper. The networks simulate the behavior model of the nonlinear amplifier through training. And then it reconstructs the nonlinear components of the self-interference signal, so that this part can be effectively eliminated.","PeriodicalId":383401,"journal":{"name":"Proceedings of the 2020 4th International Conference on Digital Signal Processing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127509650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A New Implementation of 16-bit Parallel Prefix Adder for High Speed and Low Area 一种高速低面积16位并行前缀加法器的新实现
Proceedings of the 2020 4th International Conference on Digital Signal Processing Pub Date : 2020-06-19 DOI: 10.1145/3408127.3408185
Qing-Min Liao, Shuguo Li
{"title":"A New Implementation of 16-bit Parallel Prefix Adder for High Speed and Low Area","authors":"Qing-Min Liao, Shuguo Li","doi":"10.1145/3408127.3408185","DOIUrl":"https://doi.org/10.1145/3408127.3408185","url":null,"abstract":"Adders are the most common and basic building blocks in arithmetic logic units of public-key encryption systems such as RSA. The performance of a parallel prefix adder depends on the depth of logic gates and the numbers of prefix nodes for the prefix network. In this paper, a 16-bit parallel prefix adder with new prefix network for high speed and low area is proposed. A more compact data structure is applied to reduce the size of the prefix network. Hybrid radix-2 and radix-3 prefix nodes are used to reduce logic depth on the critical path of the adder, and cloning nodes are used to avoid large fan-out. Synthesis results demonstrate that this new adder is better than industry standard Synopsys Design Compiler (DC) adder, regular adders such as Kogge--Stone and Brent-Kung adders in TSMC 28 nm technology. The 16-bit new adder is 1.14 ps faster in delay and 12.216 um2 smaller in area than Synopsys DC adder.","PeriodicalId":383401,"journal":{"name":"Proceedings of the 2020 4th International Conference on Digital Signal Processing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133893510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Distributed Algorithms for Cyclic Edge Connectivity and Cyclic Vertex Connectivity of Cubic Graphs 三次图循环边连通性和循环顶点连通性的分布式算法
Proceedings of the 2020 4th International Conference on Digital Signal Processing Pub Date : 2020-06-19 DOI: 10.1145/3408127.3408196
Jun Liang, Meixin Du, Ruihua Nie, Zhihao Liang, Zheng Li
{"title":"Distributed Algorithms for Cyclic Edge Connectivity and Cyclic Vertex Connectivity of Cubic Graphs","authors":"Jun Liang, Meixin Du, Ruihua Nie, Zhihao Liang, Zheng Li","doi":"10.1145/3408127.3408196","DOIUrl":"https://doi.org/10.1145/3408127.3408196","url":null,"abstract":"For a connected graph G, a set S of edges (vertices) is a cyclic edge (vertex) cutset if G - S is not connected and at least two components contain a cycle respectively. The cyclic edge (vertex) connectivity cλ (κ) is the cardinality of a minimum cyclic edge (vertex) cutset. In this paper, we gave distributed algorithms determining cyclic edge connectivity and cyclic vertex connectivity of cubic graphs. The experiment results showed that the distributed algorithms were significantly improved in time compared to the original algorithms when the graph was large. Time costs of the distributed algorithms separately for cyclic edge connectivity and cyclic vertex connectivity are correspondingly less than 33% and less than 40% that of the single machine algorithms when the graph was large enough.","PeriodicalId":383401,"journal":{"name":"Proceedings of the 2020 4th International Conference on Digital Signal Processing","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130276258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Working Pattern Recognition of Airborne Fire Control Radar for Unbalanced Data 机载火控雷达不平衡数据工作模式识别
Proceedings of the 2020 4th International Conference on Digital Signal Processing Pub Date : 2020-06-19 DOI: 10.1145/3408127.3408186
Yanping Liao, Xinyu Chen
{"title":"Working Pattern Recognition of Airborne Fire Control Radar for Unbalanced Data","authors":"Yanping Liao, Xinyu Chen","doi":"10.1145/3408127.3408186","DOIUrl":"https://doi.org/10.1145/3408127.3408186","url":null,"abstract":"A working pattern recognition model of airborne fire control radar for unbalanced data is proposed in this paper, which consists of weight oversampling and proportional voting random forest. Generally, there are two methods for solving the problem of the unbalanced data: data preprocessing and integrated learning. Most of the current methods have the problems such as data redundancy during oversampling, overfitting during identification, and unreasonable decision-making principles. The proposed model is made of the weight oversampling algorithm in data processing, and the proportional voting random forest in recognition algorithm. Simulation results show that, compared with traditional methods, the model proposed in this paper has greatly improved the recognition effect and recognition efficiency. It solves the problem of radar working pattern recognition in the case of unbalanced samples to a certain extent.","PeriodicalId":383401,"journal":{"name":"Proceedings of the 2020 4th International Conference on Digital Signal Processing","volume":"381 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131779681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
A Multi-dilation Convolution Neural Network for Atrial Fibrillation Detection 一种用于房颤检测的多重扩张卷积神经网络
Proceedings of the 2020 4th International Conference on Digital Signal Processing Pub Date : 2020-06-19 DOI: 10.1145/3408127.3408176
Yongfeng Huang, Jianping Lin, Guijin Wang, Zijian Ding, Li Sun
{"title":"A Multi-dilation Convolution Neural Network for Atrial Fibrillation Detection","authors":"Yongfeng Huang, Jianping Lin, Guijin Wang, Zijian Ding, Li Sun","doi":"10.1145/3408127.3408176","DOIUrl":"https://doi.org/10.1145/3408127.3408176","url":null,"abstract":"Atrial fibrillation (AF) is the most common cardiac arrhythmia whose management requires long-term automatic monitoring. The incidence of AF increases with age, causing high risks of stroke and increased morbidity and mortality. In this article, we propose a multi-dilation CNN (convolution neural network) for Atrial fibrillation detection. Our proposed model is provided with the ability to extract multi-scale features with fewer parameters by designing MSDC (multi-scale dilation convolution) blocks. The evaluation is performed on the MIT-BIH Atrial Fibrillation Database, and our multi-dilation CNN composed of MSDC blocks outperforms other methods with a sensitivity of 99.45% and specificity of 99.61%. Compared to ResNet the state of art method before, our model performs better with only a quarter parameter size of Reset, which is useful for the implementation of edge computing-based deep learning network on wearable ECG devices.","PeriodicalId":383401,"journal":{"name":"Proceedings of the 2020 4th International Conference on Digital Signal Processing","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130391843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Improvement of Deblocking Filter for AVS3 AVS3解块滤波器的改进
Proceedings of the 2020 4th International Conference on Digital Signal Processing Pub Date : 2020-06-19 DOI: 10.1145/3408127.3408141
Xi Xie, Zhenyu Wang, Ronggang Wang
{"title":"Improvement of Deblocking Filter for AVS3","authors":"Xi Xie, Zhenyu Wang, Ronggang Wang","doi":"10.1145/3408127.3408141","DOIUrl":"https://doi.org/10.1145/3408127.3408141","url":null,"abstract":"AVS3 is the third generation audio video coding standard (AVS). And the performance of AVS3 base profile is improved by 20% compared to the H.265. This paper proposes improvements to the deblocking scheme of AVS3, which has been adopted in the AVS3 baseline profile. The deblocking scheme in AVS2 has defects, including unreasonable filtering conditions and filtering coefficients. The deblocking filter in AVS3 also has the same drawback because it inherits the deblocking scheme from AVS2. These defects lead to unsatisfactory subjective quality of the AVS3 deblocking filter. Hence this paper improves the subjective quality of the AVS3 deblocking filter by reasonably modifying the filtering conditions and filter operation. In addition, to reduce the complexity of deblocking filter in AVS3, the proposed method simplifies the filtering operation of chroma deblocking. We implement the method on top of the AVS3 reference software (HPM-2.1), and the experimental result shows that subjective quality is significantly improved. The proposed method achieves 0.28% BD-rate reduction under Random Access (RA) configuration and 0.21% BD-rate reduction under ALL INTRA (AI) configuration.","PeriodicalId":383401,"journal":{"name":"Proceedings of the 2020 4th International Conference on Digital Signal Processing","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127248078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Iterative Decoding Algorithm for VDES Signals VDES信号的迭代解码算法
Proceedings of the 2020 4th International Conference on Digital Signal Processing Pub Date : 2020-06-19 DOI: 10.1145/3408127.3408158
Haosu Zhou, Bin Yue, L. Liu, Huiwen Zuo, Jiapeng Huang, Jin Wang
{"title":"Iterative Decoding Algorithm for VDES Signals","authors":"Haosu Zhou, Bin Yue, L. Liu, Huiwen Zuo, Jiapeng Huang, Jin Wang","doi":"10.1145/3408127.3408158","DOIUrl":"https://doi.org/10.1145/3408127.3408158","url":null,"abstract":"VHF data exchange system (VDES) introduces forward error correction technology, and adopts QPSK, 8PSK, 16QAM, 16APSK modulations. In this paper, an iterative decoding algorithm based on Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm and factor graph is proposed for VDES signals. Performances of the proposed iterative decoding algorithm for different modulation coding schemes are presented.","PeriodicalId":383401,"journal":{"name":"Proceedings of the 2020 4th International Conference on Digital Signal Processing","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127726070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Polarimetric Clutter Nulling Space-Time Adaptive Processing 极化杂波零化时空自适应处理
Proceedings of the 2020 4th International Conference on Digital Signal Processing Pub Date : 2020-06-19 DOI: 10.1145/3408127.3408145
K. Zhao, Zhiwen Liu, Shuli Shi, Yulin Huang, Yaxing Yue, Yougen Xu
{"title":"Polarimetric Clutter Nulling Space-Time Adaptive Processing","authors":"K. Zhao, Zhiwen Liu, Shuli Shi, Yulin Huang, Yaxing Yue, Yougen Xu","doi":"10.1145/3408127.3408145","DOIUrl":"https://doi.org/10.1145/3408127.3408145","url":null,"abstract":"A polarimetric clutter nulling based space-time adaptive processing approach is presented to weak target detection under short data samples. In the new processor, the signal under test vector is estimated via a modified least square scheme while the clutter subspace is iteratively recovered with a basis selected computationally efficient polarization-space-time sparse technique. Numerical results are given to illustrate the performance of the proposed polarimetric STAP method.","PeriodicalId":383401,"journal":{"name":"Proceedings of the 2020 4th International Conference on Digital Signal Processing","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124292829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Stable Algorithm computing high-order 3D Zernike Moments and Shape Reconstructions 一种计算高阶三维泽尼克矩和形状重建的稳定算法
Proceedings of the 2020 4th International Conference on Digital Signal Processing Pub Date : 2020-06-19 DOI: 10.1145/3408127.3408130
An-Wen Deng, Chih-Ying Gwo
{"title":"A Stable Algorithm computing high-order 3D Zernike Moments and Shape Reconstructions","authors":"An-Wen Deng, Chih-Ying Gwo","doi":"10.1145/3408127.3408130","DOIUrl":"https://doi.org/10.1145/3408127.3408130","url":null,"abstract":"3D Zernike moments are used as the 3D object shape descriptors. In this paper, we introduce a series of stable algorithms for calculating high-order the 3D Zernike moments. A kind of recurrence formula among 3D Zernike radial polynomials is presented. A voxel-based algorithm is hereby developed. The proposed method provides an accurate reconstruction image. When our algorithms are applied to the 3D object 'Einstein bust' with 100x100x100 voxels, the error rate for the shape reconstruction attains its value 0.000012 and 0 for computing all moments up to order 350 (390 respectively).","PeriodicalId":383401,"journal":{"name":"Proceedings of the 2020 4th International Conference on Digital Signal Processing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122935107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
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