检索结果-内蒙古大学图书馆

Conference on Neural, Morphological, and stochastic Methods in Image and Signal Processing

作者： RUIZ, LV PANDYA, AS FLORIDA ATLANTIC UNIV DEPT COMP SCI & ENGNBOCA RATONFL 33431

ISBN: (纸本)0819419273

A VLSI implementable, massively parallel, digital, stochastic neural network architecture with on-chip learning is described which can be used to address video/image compression applications. Color information in images is usually encoded as a means to reduce the data needed to transmit high resolution video images over a lower bandwidth communication system. A neural net approach can be used for such a compression scheme since it can be trained to map a set of patterns from a k-dimensional space to a 1D space very easily. The training algorithm is implemented as a cross correlation between previously calculated weights and global errors. These simple calculations are performed by each processing unit with information available in their local memories, thus, no transfer of information between neurons is necessary. This feature allows for the synchronous updating of all the weights, which optimizes the inherent parallel nature of the neural network architecture, making the design an excellent candidate for VLSI implementation as an SIMD architecture. By incorporating the learning portion on-chip, an appreciable reduction in computing time is possible. The stochastic nature of the learning algorithm, and a simulated 'annealing' process, allows it to convergence to a global minimum. The architecture is synthesized from an HDL description using powerful design and analysis tools which allow for many performance trade- offs and fault coverage to be done by the compiler before the final design is sent for fabrication.

关键词： ARTIFICIAL NEURAL NETWORK stochastic learning algorithm PARALLEL ARCHITECTURE HARDWARE IMPLEMENTATION

来源：评论

学校读者我要写书评

暂无评论

Interference Mitigation for Coexisting Wireless Body Area Networks: Distributed learning Solutions

引用

IEEE ACCESS 2020年 8卷 24209-24218页

作者： George, Emy Mariam Jacob, Lillykutty Natl Inst Technol Calicut Kozhikode 673601 India

When multiple wireless body area networks (WBANs) exist in close proximity to each other, the inter-user interference considerably degrades the signal to interference plus noise ratio of the packets arriving at each WBAN coordinator. Also, the propagation paths within each WBAN experience fading due to the continuous changes in the body posture and mobility of the human body. The most preferred coexisting mechanisms specified in the IEEE 802.15.6 standard is the channel hopping mechanism, which fails to consider the varying radio environment and obtained reward in its channel selection. Thus, our paper investigates this channel selection problem for interference mitigation in a time-varying environment. We formulate this channel selection problem as a finite repeated potential game and propose two learning algorithms, stochastic learning algorithm (SLA) and stochastic Estimator learning algorithm (SELA) to achieve the Nash Equilibrium (NE) of the game. Numerical results show the convergence of the learning algorithms to the NE point of the game. The performance evaluation and impact of parameters on these two algorithms are also analyzed in our paper.

关键词： Channel hopping IEEE 802 15 6 interference mitigation stochastic estimator learning algorithm stochastic learning algorithm potential game Q-learning algorithm WBAN

来源：评论

学校读者我要写书评

暂无评论

learning-Based User Clustering and Link Allocation for Content Recommendation Based on D2D Multicast Communications

引用

IEEE TRANSACTIONS ON MULTIMEDIA 2020年第8期22卷 2111-2125页

作者： Yang, Lianxin Wu, Dan Cai, Yueming Shi, Xin Wu, Yan Army Engn Univ PLA Nanjing 210007 Peoples R China

Content recommendation based on device-to-device (D2D) multicast communications is expected to become a promising approach to improve local area services. Importantly, two main challenges should be considered: i) user clustering-in order to be tailored to recommend contents, the members in the same cluster should have great similarity in multiple characteristics, and ii) link allocation-we should use as little resource consumption and information exchange as possible while keeping the recommendation accuracy. In this paper, we firstly quantify the degree of the similarity between two target users with regard to multiple characteristics. Guided by such similarity, we define a clustering validity index in terms of between-within proportion (BWP) to characterize the clustering performance. Then, the issue of user clustering is modeled as a sum BWP maximum problem, and a user clustering algorithm based on modified K-means algorithm is designed to solve it in a fast-operating and low-complexity way. After user clustering, we model the issue of link allocation as a weighted aggregate interference minimization problem, and then transform it to an exact potential game. As such, a link allocation algorithm based on stochastic learning algorithm is proposed which helps to obtain the result of this game in a distributed way without complete information. Also, we analyze its convergence and optimality performance. Simulation results demonstrate the effectiveness of our proposed algorithms.

关键词： Clustering algorithms Resource management Device-to-device communication Multicast communication Interference Multicast algorithms Games D2D multicast communications user clustering link allocation K-means algorithm stochastic learning algorithm

来源：评论

学校读者我要写书评

暂无评论

Optical-mode neural network by use of the nonlinear response of a laser diode to external optical feedback

引用

APPLIED OPTICS 1997年第26期36卷 6654-6663页

作者： Mos, EC Schleipen, JJHB deWaardt, H EINDHOVEN UNIV TECHNOL DEPT ELECT ENGNNL-5600 MB EINDHOVENNETHERLANDS

We present an intelligent all-optical neural network using a single. laser diode that is provided with controlled external feedback. The outputs of the laser neural network (LNN) are represented in the optical domain by the longitudinal cavity modes of the laser diode. The inputs to the LNN are applied by means of adjusting the external feedback of each longitudinal mode through an optical vector-matrix multiplier. Supervised training of some basic input-output mappings is demonstrated by means of a stochastic learning algorithm. The stability and reproducibility of the LNN setup is examined. (C) 1997 Optical Society of America.

关键词： optical neural networks optical computing optical feedback laser diodes stochastic learning algorithm

来源：评论

学校读者我要写书评

暂无评论

Dynamic Link Selection for Interference Mitigation in D2D Multicast Content Sharing Networks

引用

IEEE COMMUNICATIONS LETTERS 2020年第1期24卷 217-221页

作者： Yang, Lianxin Wu, Dan Zhang, Yu Yue, Chao Wu, Yan Shi, Xin Army Engn Univ PLA Nanjing 210007 Peoples R China Natl Univ Def Technol Res Inst 63 Nanjing 210007 Peoples R China

In this letter, we study the link selection problem for interference mitigation under dynamic channel conditions in D2D multicast content sharing networks. We firstly transform the problem into a stochastic game, in which the utility of each player (i.e., cluster head) is designed as the maximum expected weighted interference suffered by the receivers in the cluster. Then, we propose a simple and uncoupled link selection algorithm based on stochastic learning algorithm to obtain the Nash Equilibrium points. Importantly, the proposed algorithm only requires little intra-cluster information feedback. Theoretical analyses and numerical results validate the effectiveness of our proposed algorithm under dynamic channel conditions.

关键词： Link selection interference mitigation dynamic channel conditions stochastic game stochastic learning algorithm

来源：评论

学校读者我要写书评

暂无评论

Restricted Boltzmann machine-based cognitive protocol for secure routing in software defined wireless networks

引用

IET NETWORKS 2017年第6期6卷 162-168页

作者： MohanaPriya, Pitchai Shalinie, Selvaraj Mercy Thiagarajar Coll Engn Dept Comp Sci & Engn Madurai Tamil Nadu India

Secure and stable routing is a critical issue in a conventional network environment, as the control and data planes are integrated. An intelligent routing is highly essential to provide an attack free network to its intended users. The programmable software defined network is an emerging network paradigm in which the security policies and the forwarding rules are implemented in the controller via North Bound Interface. This study incorporates a cognitive neural network learning algorithm namely restricted Boltzmann machine (RBM), to detect the routing-based distributed denial of service attacks in dynamic source routing (DSR) protocol. RBM is a stochastic and unsupervised learning algorithm that self-learns the network conditions by using its reasoning capability and segregates malicious routes in the route cache using context-aware trust metrics such as reputation and energy consumption implemented in North Bound Application Programming Interface. The results show that a cognitive DSR protocol provides secure routing by increased packet delivery ratio, decreased end-to-end delay, reduced energy consumption and accurate detection of malicious routes compared with the conventional DSR protocol.

关键词： Boltzmann machines routing protocols telecommunication security telecommunication computing software radio radio networks unsupervised learning cache storage application program interfaces stochastic processes restricted Boltzmann machine secure routing software defined wireless networks network environment data planes control planes intelligent routing attack free network security policies forwarding rules cognitive neural network learning algorithm RBM routing-based distributed denial of service attack detection dynamic source routing protocol unsupervised learning algorithm stochastic learning algorithm route cache end-to-end delay packet delivery ratio cognitive DSR protocol north bound application programming interface energy consumption context-aware trust metrics

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：