Novel Systolization of Subquadratic Space Complexity Multipliers Based on Toeplitz Matrix–Vector Product Approach

Pan, Jeng‐Shyang; Lee, Chiou-Yng; Sghaier, Anissa; Zeghid, Medien; Xie, Jiafeng

doi:10.1109/tvlsi.2019.2903289

Cited by 112 publications

(37 citation statements)

References 28 publications

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“…The cDE algorithm inherits the probability vector (PV) and elites mechanism from rcGA [9,29]. In cDE, PV is an n * 2 matrix and is not a vector [30]:…”

Section: Compact Differential Evolution Algorithmmentioning

confidence: 99%

Parallel Compact Differential Evolution for Optimization Applied to Image Segmentation

et al. 2020

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A parallel compact Differential Evolution (pcDE) algorithm is proposed in this paper. The population is separated into multiple groups and the individual is run by using the method of compact Differential Evolution. The communication is implemented after predefined iterations. Two communication strategies are proposed in this paper. The first one is to replace the local optimal solution by global optimal solution in all groups, which is called optimal elite strategy (oe); the second one is to replace the local optimal solution by mean value of the local optimal solution in all groups, which is called mean elite strategy (me). Considering that the pcDE algorithm does not need to store a large number of solutions, the algorithm can adapt to the environment with weak computing power. In order to prove the feasibility of pcDE, several groups of comparative experiments are carried out. Simulation results based on the 25 test functions demonstrate the efficacy of the proposed two communication strategies for the pcDE. Finally, the proposed pcDE is applied to image segmentation and experimental results also demonstrate the superior quality of the pcDE compared with some existing methods.

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“…The cDE algorithm inherits the probability vector (PV) and elites mechanism from rcGA [9,29]. In cDE, PV is an n * 2 matrix and is not a vector [30]:…”

Section: Compact Differential Evolution Algorithmmentioning

confidence: 99%

Parallel Compact Differential Evolution for Optimization Applied to Image Segmentation

et al. 2020

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“…In general, when the actual wind power is low and the change is relatively stable, the prediction results are very close to the actual power; while the actual power drastically changes, they predict large deviations. Some optimization methods [48][49][50][51] may be adopted to further improve the efficiency of the proposed scheme in the future work.…”

Section: The Evaluation Performance Of Hybrid Modelmentioning

confidence: 99%

Novel Parallel Heterogeneous Meta-Heuristic and Its Communication Strategies for the Prediction of Wind Power

Pan

Chu

2019

Processes

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Wind and other renewable energy protects the ecological environment and improves economic efficiency. However, it is difficult to accurately predict wind power because of the randomness and volatility of wind. This paper proposes a new parallel heterogeneous model to predict the wind power. Parallel meta-heuristic saves computation time and improves solution quality. Four communication strategies, which include ranking, combination, dynamic change and hybrid, are introduced to balance exploration and exploitation. The dynamic change strategy is to dynamically increase or decrease the members of subgroup to keep the diversity of the population. The benchmark functions show that the algorithms have excellent performance in exploration and exploitation. In the end, they are applied to successfully realize the prediction for wind power by training the parameters of the neural network.

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“…Wireless sensor network (WSN) refers to a set of spatially dispersed and dedicated sensors for recording and monitoring the physical conditions and organizing the data collected at a central location [1,2]. WSNs are a low-cost network that is widely used in numerous applications [3][4][5]. The needed environmental information like temperature, light, sound, humidity, wind, air, and water pollution levels could be captured and measured by sensor nodes of WSN [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Identifying correctness data scheme for aggregating data in cluster heads of wireless sensor network based on naive Bayes classification

Chu

Dao

Pan

et al. 2020

J Wireless Com Network

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Wireless sensor network (WSN) has been paid more attention by scholars due to the practical communication of a system of devices to transfer information gathered from a monitored field through wireless links. Precise and accurate data of aggregating messages from sensor nodes is a vital demand for a success WSN application. This paper proposes a new scheme of identifying the correctness data scheme for aggregating data in cluster heads in hierarchical WSN based on naive Bayes classification. The collecting environmental information includes temperature, humidity, sound, and pollution levels, from sensor nodes to cluster heads that classify data fault and aggregate and transfer them to the base station. The collecting data is classified based on the classifier to aggregate in the cluster head of WSN. Compared with some existing methods, the proposed method offers an effective way of forwarding the correct data in WSN applications.

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Novel Systolization of Subquadratic Space Complexity Multipliers Based on Toeplitz Matrix–Vector Product Approach

Cited by 112 publications

References 28 publications

Parallel Compact Differential Evolution for Optimization Applied to Image Segmentation

Parallel Compact Differential Evolution for Optimization Applied to Image Segmentation

Novel Parallel Heterogeneous Meta-Heuristic and Its Communication Strategies for the Prediction of Wind Power

Identifying correctness data scheme for aggregating data in cluster heads of wireless sensor network based on naive Bayes classification

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