Hongmei Chi's research while affiliated with Huazhong Agricultural University and other places
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Publications (11)
In this study, the authors investigate the secure coding issue for a wiretap channel model with fixed main channel and varying wiretap channel, by assuming that legitimate parties can obtain the wiretapping channel state information (CSI) with some delay. For the symmetric degraded delay CSI case, they present an explicit weak security scheme by co...
The adversarial wiretap channel (AWTC) model is a secure communication model that eavesdropper can directly read and write fractions of the transmitted bits in legitimate communication. In this paper we propose a secure polar coding scheme to provide secure and reliable communication over the AWTC model. For the adversarial reading and writing acti...
![Original multi‐block chaining structure of [10]](publication/331042625/figure/fig2/AS:11431281179087598@1691151363042/Original-multi-block-chaining-structure-of10_Q320.jpg)
![Comparison between the original secure polar coding structure of [14]...](publication/331042625/figure/fig4/AS:11431281179111785@1691151363747/Comparison-between-the-original-secure-polar-coding-structure-of14-and-our-proposed_Q320.jpg)
The authors consider the problems of key exchange for one‐time pad along with the problem of rate sacrifice for secure polar coding over the two‐way wiretap channel under the strong security criterion. Based on existing techniques, they present a new hash chaining structure to solve the good bits sacrificing problem for achieving the strong securit...
Secure and reliable communication over the wiretap channel of delayed channel state information (CSI) is an important realistic subject for the study of physical layer secure coding. In this paper a communication model of this delay CSI assumption is presented on the basis of a simplified symmetric compound wiretap channel. Then on this delay CSI c...
How to represent a test sample is very crucial for linear representation based classification. The famous sparse representation focuses on employing linear combination of small samples to represent the query sample. However, the local structure and label information of data are neglected. Recently, locality-constrained collaborative representation...
We present a novel embedded conformal deep low-rank auto-encoder (ECLAE) neural network architecture for matrix recovery and it can be utilized for image restoration and clustering. Traditionally, robust principal component analysis based methods attempt to decompose the raw matrix into two components: low-rank part and sparse part. For image data...
Deep network recently has achieved promising performance for classification task with massive training samples. The behavior of this model, however, would be diminished obviously when the training set is small. Meanwhile, linear representation based classifiers have widely applied into many fields. These classifiers mostly attempt to take advantage...
The intersection graph of bases of a matroid M=(E, B) is a graph G=GI (M) with vertex set V(G) and edge set E(G) such that V(G)=B(M) and E(G)={BB′: |B ∩ B′|≠0, B, B′∈ B(M), where the same notation is used for the vertices of G and the bases of M. Suppose that |V (GI (M))| =n and k1 + k2.. kp = n, where ki is an integer, i =1, 2,.., p. In this paper...
Citations
... The study establishes the accuracy of jointly Gaussian auxiliary random variables and channel input to further evaluate the work. However, the polar coding scheme is further extended for discrete memoryless BC-CM under a more general condition [102]. Recently, Wang et al. proposed a low-complexity polar code scheme using superposition coding to improve the secrecy capacity of a WTC with a shared key between the transmitter and the authorised receiver [103]. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/693484814102529-1542351072680_Q64/Yizhi-Zhao-2.jpg)
... Recently, Yang et al. [14] extended SLCR and proposed a FR technique named sparse individual low-rank component representation (SILR) for IoT-based systems. Inspired by LRR and deep learning techniques, Xia et al. [15] developed an embedded conformal deep low-rank autoencoder (ECLAE) neural network architecture for matrix recovery. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/11431281206787964-1700893213733_Q64/Jiaxin-Cai-4.jpg)
... In order to improve the generalization capability, many methods impose constraints on representation coefficients in the field of face recognition, e.g., competitive collaborative representation classification (Co-CRC) [39], probabilistic collaborative representation classification (ProCRC) [40], and so on; the main purpose of all these methods is to make representation coefficients to be clustered in the correct class. Recently Gou et al. [41] proposed a collaborative representation model based on mean vector and weighted competition (CMWCCR) for face recognition, which adds competition, mean vector, and weighting three items as constraints of the objective function to the CRC, and considers the similarity between testing samples and the dictionary in many aspects, thus showing better classification results. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/490866767863808-1494043165620_Q64/Chunjiang-Zhang-2.jpg)
... As argued in the RBC, the localities of data are utilized for enhancing the ability of patten discrimination [16]. Recently, the representative variants of CRC are the ones that take into account the localities of data in collaborative representation [17][18][19][20][21][22][23]. Among these methods, the localities of data are often used by two aspects. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/714815815294977-1547436779329_Q64/Yinghao-Zhang-7.jpg)
