In the present investigation, we consider two new general subclasses B∑m（T, λ; α）and B^∑m （τ λ;β） of Em consisting of analytic and m-fold symmetric bi-univalent functions in the open unit disk U. For functi...In the present investigation, we consider two new general subclasses B∑m（T, λ; α）and B^∑m （τ λ;β） of Em consisting of analytic and m-fold symmetric bi-univalent functions in the open unit disk U. For functions belonging to the two classes introduced here, we derive non-sharp estimates on the initial coefficients [a-~＋ll and │a2＋1│. Several connections to some of the earlier known results are also pointed out.展开更多
In this paper, we investigate the coefficient estimates of a class of m-fold bi-univalent function de?ned by subordination. The results presented in this paper improve or generalize the recent works of other authors.
In this paper, we investigate the coefficient estimate and Fekete-Szeg? inequality of a class of m-fold bi-univalent function defined by subordination. The results presented in this paper improve or generalize the rec...In this paper, we investigate the coefficient estimate and Fekete-Szeg? inequality of a class of m-fold bi-univalent function defined by subordination. The results presented in this paper improve or generalize the recent works of other authors.展开更多
Let {Xm（t）, t∈R＋} be an m-Fold integrated Brownian motion. In this paper, with the help of small ball probability estimate, a functional law of the iterated logarithm （LIL） for Xm（t） is established. This exten...Let {Xm（t）, t∈R＋} be an m-Fold integrated Brownian motion. In this paper, with the help of small ball probability estimate, a functional law of the iterated logarithm （LIL） for Xm（t） is established. This extends the classic Chung type liminf result for this process. Furthermore, a result about the weighted occupation measure for Xm（t） is also obtained.展开更多
(Aim)Chinese sign language is an essential tool for hearing-impaired to live,learn and communicate in deaf communities.Moreover,Chinese sign language plays a significant role in speech therapy and rehabilitation.Chine...(Aim)Chinese sign language is an essential tool for hearing-impaired to live,learn and communicate in deaf communities.Moreover,Chinese sign language plays a significant role in speech therapy and rehabilitation.Chinese sign language identification can provide convenience for those hearing impaired people and eliminate the communication barrier between the deaf community and the rest of society.Similar to the research of many biomedical image processing(such as automatic chest radiograph processing,diagnosis of chest radiological images,etc.),with the rapid development of artificial intelligence,especially deep learning technologies and algorithms,sign language image recognition ushered in the spring.This study aims to propose a novel sign language image recognition method based on an optimized convolutional neural network.(Method)Three different combinations of blocks:Conv-BN-ReLU-Pooling,Conv-BN-ReLU,Conv-BN-ReLU-BN were employed,including some advanced technologies such as batch normalization,dropout,and Leaky ReLU.We proposed an optimized convolutional neural network to identify 1320 sign language images,which was called as CNN-CB method.Totally ten runs were implemented with the hold-out randomly set for each run.(Results)The results indicate that our CNN-CB method gained an overall accuracy of 94.88±0.99%.(Conclusion)Our CNN-CB method is superior to thirteen state-of-the-art methods:eight traditional machine learning approaches and five modern convolutional neural network approaches.展开更多
文摘In the present investigation, we consider two new general subclasses B∑m（T, λ; α）and B^∑m （τ λ;β） of Em consisting of analytic and m-fold symmetric bi-univalent functions in the open unit disk U. For functions belonging to the two classes introduced here, we derive non-sharp estimates on the initial coefficients [a-~＋ll and │a2＋1│. Several connections to some of the earlier known results are also pointed out.
基金The NSF(KJ2018A0839,KJ2018A0833) of Anhui Provincial Department of Education
文摘In this paper, we investigate the coefficient estimates of a class of m-fold bi-univalent function de?ned by subordination. The results presented in this paper improve or generalize the recent works of other authors.
基金This work was supported by the NSFC(Grant No.19801012)the Natural Science Foundation of Hunan Province and the Ministry of Education of China.([2000],65)
基金Supported by the National Natural Science Foundation of China(Grant Nos.1156100111271045)+4 种基金the Program for Young Talents of Science and Technology in Universities of Inner Mongolia Autonomous Region(Grant No.NJYT-18-A14)the Natural Science Foundation of Inner Mongolia of China(Grant No.2018MS01026)the Higher School Foundation of Inner Mongolia of China(Grant No.NJZY19211)the Natural Science Foundation of Anhui Provincial Department of Education(Grant Nos.KJ2018A0833 KJ2018A0839)
文摘In this paper, we investigate the coefficient estimate and Fekete-Szeg? inequality of a class of m-fold bi-univalent function defined by subordination. The results presented in this paper improve or generalize the recent works of other authors.
基金Project supported by the National Natural Science Foundation of China (No.10131040)the Specialized Research Fund for the Doctor Program of Higher Education (No.2002335090).
文摘Let {Xm（t）, t∈R＋} be an m-Fold integrated Brownian motion. In this paper, with the help of small ball probability estimate, a functional law of the iterated logarithm （LIL） for Xm（t） is established. This extends the classic Chung type liminf result for this process. Furthermore, a result about the weighted occupation measure for Xm（t） is also obtained.
基金supported from The National Philosophy and Social Sciences Foundation(Grant No.20BTQ065).
文摘(Aim)Chinese sign language is an essential tool for hearing-impaired to live,learn and communicate in deaf communities.Moreover,Chinese sign language plays a significant role in speech therapy and rehabilitation.Chinese sign language identification can provide convenience for those hearing impaired people and eliminate the communication barrier between the deaf community and the rest of society.Similar to the research of many biomedical image processing(such as automatic chest radiograph processing,diagnosis of chest radiological images,etc.),with the rapid development of artificial intelligence,especially deep learning technologies and algorithms,sign language image recognition ushered in the spring.This study aims to propose a novel sign language image recognition method based on an optimized convolutional neural network.(Method)Three different combinations of blocks:Conv-BN-ReLU-Pooling,Conv-BN-ReLU,Conv-BN-ReLU-BN were employed,including some advanced technologies such as batch normalization,dropout,and Leaky ReLU.We proposed an optimized convolutional neural network to identify 1320 sign language images,which was called as CNN-CB method.Totally ten runs were implemented with the hold-out randomly set for each run.(Results)The results indicate that our CNN-CB method gained an overall accuracy of 94.88±0.99%.(Conclusion)Our CNN-CB method is superior to thirteen state-of-the-art methods:eight traditional machine learning approaches and five modern convolutional neural network approaches.
