http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Wenzhun HUANG (검색결과 3 건)
- 무료
- 기관 내 무료
- 유료
-
Wenzhun Huang,Shanwen Zhang 보안공학연구지원센터 2016 International Journal of Future Generation Communi Vol.9 No.3
In this paper, we conduct research on the wireless sensor network management methods based on the runtime model. With the deepening of the research, scalability and maintainability of wireless sensor network has become an important target of its application promotion. Consider that the nodes randomly distributed monitoring area, looking for a complete coverage of this area several disjoint nodes which uses genetic algorithm to optimize the network survival time nodes and corresponding coverage. From the point of view of software engineering, most of the specific software system knowledge hidden in the program and document, the model as the main content of the document and procedures of high-level abstractions. The management of the network is urgently needed. As the additional research, we also conduct theoretical analysis on the wireless sensor network security enhancement methodology with the tradition game theory and mathematical optimization approaches which will be meaningful. Game theory is on the interaction between much of decision-making behavior has, according to the different subjects in the control information and the cognition of their own capabilities which will be a novel method for the analysis. The numerical simulation shows that our method performed better compared with other related approaches. In the future, more research will be conducted to polish the current method.
-
Wenzhun Huang,Shanwen Zhang 보안공학연구지원센터 2016 International Journal of Future Generation Communi Vol.9 No.3
In this paper, the performance of the single-estimation and multiple-estimation is investigated in multiple-input multiple-output (MIMO) Rician flat fading channels using the traditional least squares estimator and the Bayesian minimum mean square error estimator. In high-speed mobile environment, relatively severe channel conditions change, at this point, the sender is difficult to obtain more accurate of the instantaneous channel state information, for the implementation of adaptive MIMO transmission under this scenario. The MIMO techniques can be combined with space-time coding technique for coding diversity gain and also can use a simple multiplexing transmission in order to improve the transmission rate. The pseudo random sequence is certain, but it has many properties similar to that of the random binary data. Such as any two pseudo random sequence of cross correlation is small. In the research, we combine the basic theory of the state-of-the algorithm to propose our method. In the experimental part, we compare our method with other related state-of-the-art algorithms. The result proves the effectiveness and feasibility of the proposed method. In the near future, we plan to conduct more literature review and theoretical analysis to modify and optimize our current method.
-
Jianping PAN,Wenzhun HUANG,Shanwen ZHANG 보안공학연구지원센터 2016 International Journal of Future Generation Communi Vol.9 No.10
In this paper, we conduct research on issues related to the primary features of the Internet of things system and the corresponding data communication characteristics based on sparse coding and joint deep neural network. Internet of things is more than the underlying device difference communication method and it is the Internet of things needs to study in the field of hot issue. Using traditional algorithm for Internet communication equipment need particle filter was carried out on the acquisition of communication signal processing. Communication technology enables the Internet of things will perceive the information between different terminals for efficient transmission and exchange, exchange and sharing and the information resources is the key to the functions of things. To enhance the robustness and efficiency of the current IOT systems, we adopt the sparse coded dictionary learning theory to detect the size of the data and optimize the compressive sensing technique to modify the resolution. With the advances of the deep neural network, we analyze the topology of the system network structure and extract the pattern features and characteristics to make the signal transmission process more quickly and feasible. To enhance the objective function, we obtain the restricted optimization algorithm to help terminate the iteration for the higher efficiency. In the final part, we simulation our algorithm for times compared with other well-performed approaches. The result indicates that our method outperforms both in the accuracy layer an in the time-consuming layer which will hold specific meaning.
연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
