We explore the stability of image reconstruction algorithms under deterministic compressed sensing. Recently, we have proposed [1-3] deterministic compressed sensing algorithms for 2D images. These algorithms are suit...We explore the stability of image reconstruction algorithms under deterministic compressed sensing. Recently, we have proposed [1-3] deterministic compressed sensing algorithms for 2D images. These algorithms are suitable when Daubechies wavelets are used as the sparsifying basis. In the initial work, we have shown that the algorithms perform well for images with sparse wavelets coefficients. In this work, we address the question of robustness and stability of the algorithms, specifically, if the image is not sparse and/or if noise is present. We show that our algorithms perform very well in the presence of a certain degree of noise. This is especially important for MRI and other real world applications where some level of noise is always present.展开更多
Based on a learner corpus Chinese Learner English Corpus(CLEC)and a native speaker corpus Freiburg Brown Corpus of American English(FROWN),this research investigates the differences between Chinese learners of English...Based on a learner corpus Chinese Learner English Corpus(CLEC)and a native speaker corpus Freiburg Brown Corpus of American English(FROWN),this research investigates the differences between Chinese learners of English and English native speakers in their knowledge of the metonymic senses of human body word“hand”.Two research questions are raised:(1)What are the features that distinguish Chinese English learners from English native speakers?(2)What are the rules in learners’learning of English metonymic senses?In order to answer these two questions,this paper has investigated the frequencies of the identified senses in two corpora of FROWN and CLEC,and the sequence of learning metonymic senses.The results show that Chinese learner’s knowledge of metonymic senses of“hand”is restricted to fixed phrases,especially verb phrases.It is also found that in the process of English learning,learners do have some preferences for basic sense,and then they learn peripheral senses by reciting some fixed phrases.展开更多
Studies have indicated that the distributed compressed sensing based(DCSbased) channel estimation can decrease the length of the reference signals effectively. In block transmission, a unique word(UW) can be used as a...Studies have indicated that the distributed compressed sensing based(DCSbased) channel estimation can decrease the length of the reference signals effectively. In block transmission, a unique word(UW) can be used as a cyclic prefix and reference signal. However, the DCS-based channel estimation requires diversity sequences instead of UW. In this paper, we proposed a novel method that employs a training sequence(TS) whose duration time is slightly longer than the maximum delay spread time. Based on proposed TS, the DCS approach perform perfectly in multipath channel estimation. Meanwhile, a cyclic prefix construct could be formed, which reduces the complexity of the frequency domain equalization(FDE) directly. Simulation results demonstrate that, by using the method of simultaneous orthogonal matching pursuit(SOMP), the required channel overhead has been reduced thanks to the proposed TS.展开更多
In the Digital World scenario,the confidentiality of information in video transmission plays an important role.Chaotic systems have been shown to be effective for video signal encryption.To improve video transmission ...In the Digital World scenario,the confidentiality of information in video transmission plays an important role.Chaotic systems have been shown to be effective for video signal encryption.To improve video transmission secrecy,compressive encryption method is proposed to accomplish compression and encryption based on fractional order hyper chaotic system that incorporates Compressive Sensing(CS),pixel level,bit level scrambling and nucleotide Sequences operations.The measurement matrix generates by the fractional order hyper chaotic system strengthens the efficiency of the encryption process.To avoid plain text attack,the CS measurement is scrambled to its pixel level,bit level scrambling decreases the similarity between the adjacent measurements and the nucleotide sequence operations are done on the scrambled bits,increasing the encryption.Two stages are comprised in the reconstruction technique,the first stage uses the intra-frame similarity and offers robust preliminary retrieval for each frame,and the second stage iteratively improves the efficiency of reconstruction by integrating inter frame Multi Hypothesis(MH)estimation and weighted residual sparsity modeling.In each iteration,the residual coefficient weights are modified using a mathematical approach based on the MH predictions,and the Split Bregman iteration algorithm is defined to resolve weighted l1 regularization.Experimental findings show that the proposed algorithm provides good compression of video coupled with an efficient encryption method that is resistant to multiple attacks.展开更多
Due to the low sound propagation speed, the tradeoff between high azimuth resolution and wide imaging swath has severely limited the application of sonar underwater target imaging. However, based on compressed sensing...Due to the low sound propagation speed, the tradeoff between high azimuth resolution and wide imaging swath has severely limited the application of sonar underwater target imaging. However, based on compressed sensing(CS) technique, it is feasible to image targets with merely one pulse and thus avoid the above tradeoff. To investigate the possible waveforms for CS-based underwater imaging, the deterministic M sequences widely used in sonar applications are introduced in this paper. By analyzing the compressive matrix constructed from M sequences, the coherence parameter and the restricted isometry property(RIP) of the matrix are derived. Also, the feasibility and advances of M sequence are demonstrated by being compared with the existing Alltop sequence in underwater CS imaging framework. Finally, the results of numerical simulations and a real experiment are provided to reveal the effectiveness of the proposed signal.展开更多
文摘We explore the stability of image reconstruction algorithms under deterministic compressed sensing. Recently, we have proposed [1-3] deterministic compressed sensing algorithms for 2D images. These algorithms are suitable when Daubechies wavelets are used as the sparsifying basis. In the initial work, we have shown that the algorithms perform well for images with sparse wavelets coefficients. In this work, we address the question of robustness and stability of the algorithms, specifically, if the image is not sparse and/or if noise is present. We show that our algorithms perform very well in the presence of a certain degree of noise. This is especially important for MRI and other real world applications where some level of noise is always present.
基金Supported by the National Natural Science Foundation of China（No.60832009）, the Natural Science Foundation of Beijing （No.4102044） and the National Nature Science Foundation for Young Scholars of China （No.61001115）
文摘Based on a learner corpus Chinese Learner English Corpus(CLEC)and a native speaker corpus Freiburg Brown Corpus of American English(FROWN),this research investigates the differences between Chinese learners of English and English native speakers in their knowledge of the metonymic senses of human body word“hand”.Two research questions are raised:(1)What are the features that distinguish Chinese English learners from English native speakers?(2)What are the rules in learners’learning of English metonymic senses?In order to answer these two questions,this paper has investigated the frequencies of the identified senses in two corpora of FROWN and CLEC,and the sequence of learning metonymic senses.The results show that Chinese learner’s knowledge of metonymic senses of“hand”is restricted to fixed phrases,especially verb phrases.It is also found that in the process of English learning,learners do have some preferences for basic sense,and then they learn peripheral senses by reciting some fixed phrases.
基金support by National Key Technology Research and Development Program of the Ministry of Science and Technology of China (2015BAK05B01)
文摘Studies have indicated that the distributed compressed sensing based(DCSbased) channel estimation can decrease the length of the reference signals effectively. In block transmission, a unique word(UW) can be used as a cyclic prefix and reference signal. However, the DCS-based channel estimation requires diversity sequences instead of UW. In this paper, we proposed a novel method that employs a training sequence(TS) whose duration time is slightly longer than the maximum delay spread time. Based on proposed TS, the DCS approach perform perfectly in multipath channel estimation. Meanwhile, a cyclic prefix construct could be formed, which reduces the complexity of the frequency domain equalization(FDE) directly. Simulation results demonstrate that, by using the method of simultaneous orthogonal matching pursuit(SOMP), the required channel overhead has been reduced thanks to the proposed TS.
文摘In the Digital World scenario,the confidentiality of information in video transmission plays an important role.Chaotic systems have been shown to be effective for video signal encryption.To improve video transmission secrecy,compressive encryption method is proposed to accomplish compression and encryption based on fractional order hyper chaotic system that incorporates Compressive Sensing(CS),pixel level,bit level scrambling and nucleotide Sequences operations.The measurement matrix generates by the fractional order hyper chaotic system strengthens the efficiency of the encryption process.To avoid plain text attack,the CS measurement is scrambled to its pixel level,bit level scrambling decreases the similarity between the adjacent measurements and the nucleotide sequence operations are done on the scrambled bits,increasing the encryption.Two stages are comprised in the reconstruction technique,the first stage uses the intra-frame similarity and offers robust preliminary retrieval for each frame,and the second stage iteratively improves the efficiency of reconstruction by integrating inter frame Multi Hypothesis(MH)estimation and weighted residual sparsity modeling.In each iteration,the residual coefficient weights are modified using a mathematical approach based on the MH predictions,and the Split Bregman iteration algorithm is defined to resolve weighted l1 regularization.Experimental findings show that the proposed algorithm provides good compression of video coupled with an efficient encryption method that is resistant to multiple attacks.
基金supported in part by National Natural Science Foundation of China (Grant No. 61271391)111 Project of China Ministry of Education (MOE) (Grant No. B14010)+2 种基金New Century Excellent Talents Supporting Plan of China MOE (Grant No. NCET-13-0049)Ministry Research Foundation (Grant No. 9140A21050114HT05338)Outstanding Youth Teacher Training Plan of BIT (Grant No. BIT-JC-201205)
文摘Due to the low sound propagation speed, the tradeoff between high azimuth resolution and wide imaging swath has severely limited the application of sonar underwater target imaging. However, based on compressed sensing(CS) technique, it is feasible to image targets with merely one pulse and thus avoid the above tradeoff. To investigate the possible waveforms for CS-based underwater imaging, the deterministic M sequences widely used in sonar applications are introduced in this paper. By analyzing the compressive matrix constructed from M sequences, the coherence parameter and the restricted isometry property(RIP) of the matrix are derived. Also, the feasibility and advances of M sequence are demonstrated by being compared with the existing Alltop sequence in underwater CS imaging framework. Finally, the results of numerical simulations and a real experiment are provided to reveal the effectiveness of the proposed signal.
