作者机构：
[Zhao, Jiemei] Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430023, Peoples R China.
通讯机构：
[Zhao, Jiemei] W;Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430023, Peoples R China.
摘要：
Dear editor,
As a consequence of symmetry arguments,the memristor was predicted by Chua[1].As the fourth basic circuit element,its memory characteristic and nanometer dimen-sions are devoid of resistors,capacitors,and inductors.In the field of the dynamical behavior analysis for memristive neural networks(MNNs),information exchange and signal transmission among different neurons are time-varying ac-tivities and discrete time delays are frequently supposed to be bounded,which implies that the current state of a neuron depend only on a part of its history.Actually,the current behavior of a neuron depends upon all its historical infor-mation.Consequently,discrete time delays in MNNs should be assumed to be time-varying and unbounded,which can exhibit the characteristics of the neurons in human brains.Many outstanding achievements on MNNs have already been investigated,but the discrete time delays of the in-vestigated MNNs were all assumed to be bounded[2-4].
摘要：
Sparse representation has been in a widespread use in hyperspectral image (HSI) classification task. The samples to be classified can be linearly represented with a few samples from the same class. However, when samples from different classes are highly correlated with each other, it makes the classification task challenging. To solve this problem, we take the Euclidean distance information between the training samples and testing samples into consideration to construct a new dictionary for sparse representation. That is, we propose a locality-constrained sparse representation classifier (LSRC) in this paper. First, the K nearest neighbour (KNN) algorithm is applied to the training data set to form a locality constrained dictionary by excluding the samples separated from testing samples in the Euclidean space. Then, the sparse coding is applied to the testing sample with the formed dictionary via class dependent orthogonal matching pursuit (OMP) algorithm which utilizes the class label information. Finally, by using the minimal residual rule within all catergories, we can obtain class label of the testing sample. Experiments based on the chosen three hyperspectral datasets prove that our proposed LSRC outperforms other popular classifiers. (c) 2020 Elsevier Inc. All rights reserved.
作者机构：
[Zou, YiLin; Zhou, Kang; Zhen, YiTing] School of Math and Computer, Wuhan Polytechnic University, Wuhan;Hubei;430023, China;[Ji, BinGe] School of Economics and Management, Wuhan Polytechnic University, Wuhan;[Wu, XiaoDong] School of Electrical and Electronic Engineering, Wuhan Polytechnic University, Wuhan
通讯机构：
[Kang Zhou] S;School of Math and Computer, Wuhan Polytechnic University, Wuhan, China
关键词：
Dichotomy method;Finite difference method;One-dimensional unsteady heat conduction;Thickness optimization of high temperature protective clothing
摘要：
This paper explores conditional image generation with a One-Vs-All classifier based on the Generative Adversarial Networks (GANs). Instead of the real/fake discriminator used in vanilla GANs, we propose to extend the discriminator to a One-Vs-All classifier (GAN-OVA) that can distinguish each input data to its category label. Specifically, we feed certain additional information as conditions to the generator and take the discriminator as a One-Vs-All classifier to identify each conditional category. Our model can be applied to different divergence or distances used to define the objective function, such as Jensen-Shannon divergence and Earth-Mover (or called Wasserstein-1) distance. We evaluate GANOVAs on MNIST and CelebA-HQ datasets, and the experimental results show that GAN-OVAs improve generation quality and the stability of training. (c) 2021 Elsevier B.V. All rights reserved.
期刊：
Cryptography and Communications,2021年13(1):1-14 ISSN：1936-2447
通讯作者：
Luo, Jinquan
作者机构：
[Fang, Xiaolei; Luo, Jinquan; Liu, Meiqing] Cent China Normal Univ, Sch Math & Stat, Wuhan 430079, Peoples R China.;[Fang, Xiaolei; Luo, Jinquan; Liu, Meiqing] Cent China Normal Univ, Hubei Key Lab Math Sci, Wuhan 430079, Peoples R China.;[Fang, Xiaolei] Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430048, Peoples R China.
通讯机构：
[Luo, Jinquan] C;Cent China Normal Univ, Sch Math & Stat, Wuhan 430079, Peoples R China.;Cent China Normal Univ, Hubei Key Lab Math Sci, Wuhan 430079, Peoples R China.
摘要：
In this paper, we propose a mechanism for the construction of MDS codes with arbitrary dimensions of Euclidean hulls. Precisely, we construct (extended) generalized Reed-Solomon (GRS) codes with assigned dimensions of Euclidean hulls from self-orthogonal GRS codes. It turns out our constructions are more general than previous works on Euclidean hulls of (extended) GRS codes.
期刊：
Mathematical Problems in Engineering,2021年2021 ISSN：1024-123X
作者机构：
[Yang, M. J.; Sun, C. Q.; Liu, R. F.] Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430023, Peoples R China.;[Zeng, S.] Wuhan Polytech Univ, Sch Econ & Management, Wuhan 430023, Peoples R China.
摘要：
The research about online monitoring and leakage automatic location of water distribution networks (WDN) has a wide range of applications that include water resource protection, monitoring, and allocation. Variational mode decomposition (VMD) and cross-correlation (CC) based leakage location is a popular and effective method in WDN. However, the value of K intrinsic mode functions (IMFs) based on VMD decomposition needs to be determined artificially, which affects the separation effect of signal frequency band characteristics directly. Hence, this work proposes an adaptive method to determine the parameter K of leakage vibration signal's IMFs, which will be applied to automatic leakage location in WDN. Firstly, the number of saddle points in the frequency domain envelope of the sampled signal in different step sizes is calculated. The parameter K is determined according to the curvature change of the number of saddle points and the sampled signal. Finally, the selective IMFs are reconstituted into a new signal, which can determine a leak position using CC based time-delay estimation (TDE). To verify the effectiveness of the proposed algorithm, the different methods based on EMD and Fast ICA are compared. The experimental results demonstrate that the proposed parameter K value adaptive VMD (KVA-VMD) decomposition method is more suitable for leakage location in WDN.
