Journal ArticleDOI
Routing Algorithm Based on Delay Rate in Wireless Cognitive Radio Network
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TLDR
Experimental results show that the proposed real-time routing algorithm in spectrum network can obtain a lower end-to-end average delay and improves network throughput and the steady and reliability of the link connection.Abstract:
To reduce the end-to-end average delay of algorithm in wireless network, this paper proposes the real-time routing algorithm in spectrum network. It is analyzed that the dynamic changes of the radio network model and routing algorithm in spectrum network. Through using Markov state transition and adjusting the router with scaling factor, the high-quality resources in the network can be obtained and fully utilized, and then these can reduce the transmission time latency rate and timely adjust the route. After that the tendency of spectrum network and specific real-time algorithm are given. Finally, by using the network simulation NS-2, simulation experiments are used to estimate the performance test. Experimental results show that compared with the traditional algorithm, the proposed algorithm can obtain a lower end-to-end average delay and improves network throughput and the steady and reliability of the link connection.read more
Citations
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Journal ArticleDOI
Hidden Markov Model based channel selection framework for cognitive radio network
S Senthilkumar,C. Geetha Priya +1 more
TL;DR: A Hidden Markov Model (HMM)-based channel selection framework is introduced to minimize the delay occurred during the channel search and optimize the range of the spectrum band and exhibit better end-to-end throughput, bandwidth-power product and lower running time, energy consumption, and average end- to-end delay when compared to the existing schemes.
Journal ArticleDOI
A review of channel estimation and security techniques for CRNS
S Senthilkumar,C. Geetha Priya +1 more
TL;DR: From the surveyed results, it is observed that the existing spectrum sensing, and prediction-based techniques consume more energy, and minimal data transmission rate for detecting the idle channel, and the end-to-end delay, energy consumption, end- to- end delay, and bandwidth are not minimized by the existing techniques.
Journal ArticleDOI
Prediction Simulation Study of Road Traffic Carbon Emission Based on Chaos Theory and Neural Network
Hao Wu,Xianglian Zhao +1 more
TL;DR: The simulation result shows that, Chao-BPNN has overcome the deficits of the traditional method and could precisely and comprehensively reflect the change rules of the road traffic carbon emission time sequence, and effectively improved the prediction precision of the Road Traffic carbon emission.
Journal ArticleDOI
The Intelligent Task Scheduling Algorithm in Cloud Computing with Multistage Optimization
TL;DR: The experimental results show that under the same conditions, the total task completion time of improved algorithm has been reduced and its performance advantage are getting more obvious with the increased task measures.
Journal ArticleDOI
Urban Real-Time Traffic Monitoring Method Based on the Simplified Network Model
Wei Rong,Shen Xibing,Yang Yi +2 more
TL;DR: In urban real-time traffic monitoring, due to the difficult of delay time acquisition at intersection, complicated calculation model, lead to inaccurate traffic discriminant, a real- Time Traffic discriminant method based on the simplified network model is proposed.
References
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Book
Compressed sensing
TL;DR: It is possible to design n=O(Nlog(m)) nonadaptive measurements allowing reconstruction with accuracy comparable to that attainable with direct knowledge of the N most important coefficients, and a good approximation to those N important coefficients is extracted from the n measurements by solving a linear program-Basis Pursuit in signal processing.
Journal ArticleDOI
Robust Face Recognition via Sparse Representation
TL;DR: This work considers the problem of automatically recognizing human faces from frontal views with varying expression and illumination, as well as occlusion and disguise, and proposes a general classification algorithm for (image-based) object recognition based on a sparse representation computed by C1-minimization.
Proceedings ArticleDOI
Discriminative K-SVD for dictionary learning in face recognition
Qiang Zhang,Baoxin Li +1 more
TL;DR: The proposed method to learn an over-complete dictionary is based on extending the K-SVD algorithm by incorporating the classification error into the objective function, thus allowing the performance of a linear classifier and the representational power of the dictionary being considered at the same time by the same optimization procedure.
Book ChapterDOI
Gabor feature based sparse representation for face recognition with gabor occlusion dictionary
Meng Yang,Lei Zhang +1 more
TL;DR: The number of atoms is significantly reduced in the computed Gabor occlusion dictionary, which greatly reduces the computational cost in coding the occluded face images while improving greatly the SRC accuracy.
Proceedings ArticleDOI
Towards a practical face recognition system: Robust registration and illumination by sparse representation
TL;DR: It is shown that the proposed simple and practical face recognition system can efficiently and effectively recognize faces under a variety of realistic conditions, using only frontal images under the proposed illuminations as training.