Pub Date : 2015-01-25DOI: 10.3969/J.ISSN.1001-0548.2015.01.003
Xiaofeng Li, L. Zeng, Jin Xu, Shiping Ma
Recently, the super-resolution methods based on sparse representation has became a research hotpot in signal processing. How to calculate the sparse coefficients fast and accurately is the key of sparse representation algorithm. In this paper, we propose a feature sign method to compute the sparse coefficients in the search step. Inspired by the compressed sensing theory, two dictionaries are jointly learnt to conduct super-resolution in this method. The feature sign algorithm changes the non-convex problem to a convex one by guessing the sign of the sparse coefficient at each iteration. It improves the accuracy of the obtained sparse coefficients and speeds the algorithm. Simulation results show that the proposed scheme outperforms the interpolation methods and classic sparse representation algorithms in both subjective inspects and quantitative evaluations.
{"title":"Single Image Super-Resolution Based on the Feature Sign Method","authors":"Xiaofeng Li, L. Zeng, Jin Xu, Shiping Ma","doi":"10.3969/J.ISSN.1001-0548.2015.01.003","DOIUrl":"https://doi.org/10.3969/J.ISSN.1001-0548.2015.01.003","url":null,"abstract":"Recently, the super-resolution methods based on sparse representation has became a research hotpot in signal processing. How to calculate the sparse coefficients fast and accurately is the key of sparse representation algorithm. In this paper, we propose a feature sign method to compute the sparse coefficients in the search step. Inspired by the compressed sensing theory, two dictionaries are jointly learnt to conduct super-resolution in this method. The feature sign algorithm changes the non-convex problem to a convex one by guessing the sign of the sparse coefficient at each iteration. It improves the accuracy of the obtained sparse coefficients and speeds the algorithm. Simulation results show that the proposed scheme outperforms the interpolation methods and classic sparse representation algorithms in both subjective inspects and quantitative evaluations.","PeriodicalId":35864,"journal":{"name":"电子科技大学学报","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70067751","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}
Pub Date : 2015-01-01DOI: 10.3969/J.ISSN.1001-0548.2015.02.014
Kuojun Yang, Shulin Tian, Jinpeng Song, Jiang Jun
The application of three-dimensional mapping technology has improved the waveform capture rate of digital storage oscilloscopes(DSO), however it does not eliminate the dead time of DSO. In this research, a new 3D-imaging method, fragmentation and centralized mapping, is proposed. It divides high-speed large capacity dynamic memory(DDR3 SDRAM) into several regions based on the time-base. In each region, the waveforms with the same triggering condition are stored, and the waveforms will be post-processed with three-dimensional mapping Technology. Dual-port RAM based fast waveform mapping technology and parallel waveform mapping technology decrease the mapping time greatly. This method guarantees high waveform capture rate and enable larger data storage capacity. It also enables seamless acquisition for the duration of each stored waveform. By mathematical modeling, it can be proven that our system can capture the sporadic transient event in shorter time. Through double pulse test method, it can be demonstrated that the highest capture rate of the system is measured to be 6 250 000 wfms/s. After analysis, it is obtained that the ratio of dead time is reduced to 43.86%.
{"title":"A three-dimensional mapping method based on fragmentation","authors":"Kuojun Yang, Shulin Tian, Jinpeng Song, Jiang Jun","doi":"10.3969/J.ISSN.1001-0548.2015.02.014","DOIUrl":"https://doi.org/10.3969/J.ISSN.1001-0548.2015.02.014","url":null,"abstract":"The application of three-dimensional mapping technology has improved the waveform capture rate of digital storage oscilloscopes(DSO), however it does not eliminate the dead time of DSO. In this research, a new 3D-imaging method, fragmentation and centralized mapping, is proposed. It divides high-speed large capacity dynamic memory(DDR3 SDRAM) into several regions based on the time-base. In each region, the waveforms with the same triggering condition are stored, and the waveforms will be post-processed with three-dimensional mapping Technology. Dual-port RAM based fast waveform mapping technology and parallel waveform mapping technology decrease the mapping time greatly. This method guarantees high waveform capture rate and enable larger data storage capacity. It also enables seamless acquisition for the duration of each stored waveform. By mathematical modeling, it can be proven that our system can capture the sporadic transient event in shorter time. Through double pulse test method, it can be demonstrated that the highest capture rate of the system is measured to be 6 250 000 wfms/s. After analysis, it is obtained that the ratio of dead time is reduced to 43.86%.","PeriodicalId":35864,"journal":{"name":"电子科技大学学报","volume":"44 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70067816","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}
Pub Date : 2013-10-15DOI: 10.3969/J.ISSN.1001-0548.2013.05.024
Wang Jian-chen, Jin Zong-xin
The biological immune system when attacked can always find the right antibodies to destroy the antigen and can maintain the diversity of antibodies. The combination of genetic and immunity in biology has been shown to be an effective approach to solving the degeneration of genetic algorithm in the late iterative optimization. According to the characteristic that the injected vaccine immune system can accomplish quickly identification the antigen, an improved immune genetic algorithm (IIGA) is proposed based on this theory for Benchmark function optimization. The results show that the IIGA can effectively prevent the algorithm degenerative during the process of optimization of the genetic algorithm, and improve the convergent speed of the algorithm.
{"title":"Improvement of Immune Genetic Algorithm for Multi-Peak Function Optimization","authors":"Wang Jian-chen, Jin Zong-xin","doi":"10.3969/J.ISSN.1001-0548.2013.05.024","DOIUrl":"https://doi.org/10.3969/J.ISSN.1001-0548.2013.05.024","url":null,"abstract":"The biological immune system when attacked can always find the right antibodies to destroy the antigen and can maintain the diversity of antibodies. The combination of genetic and immunity in biology has been shown to be an effective approach to solving the degeneration of genetic algorithm in the late iterative optimization. According to the characteristic that the injected vaccine immune system can accomplish quickly identification the antigen, an improved immune genetic algorithm (IIGA) is proposed based on this theory for Benchmark function optimization. The results show that the IIGA can effectively prevent the algorithm degenerative during the process of optimization of the genetic algorithm, and improve the convergent speed of the algorithm.","PeriodicalId":35864,"journal":{"name":"电子科技大学学报","volume":"42 1","pages":"769-772"},"PeriodicalIF":0.0,"publicationDate":"2013-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70067740","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}
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