By Tao Tao, Zhenming Peng, Chaonan Yang, Fang Wei (auth.), Min Zhu (eds.)
This quantity contains prolonged and revised models of a collection of chosen papers from the foreign convention on electrical and Electronics (EEIC 2011) , hung on June 20-22 , 2011, that's together equipped via Nanchang collage, Springer, and IEEE IAS Nanchang Chapter.
The goal of EEIC 2011 quantity 2 is to supply an important interdisciplinary discussion board for the presentation of recent ways from electric engineering and controls, to foster integration of the newest advancements in medical learn. 133 similar subject papers have been chosen into this quantity. all of the papers have been reviewed by way of 2 application committee contributors and chosen by means of the quantity editor Prof. Min Zhu.
We wish each player could have an excellent chance to switch their examine principles and effects and to debate the state-of-the-art within the components of engineering and controls.
Read or Download Electrical Engineering and Control: Selected Papers from the 2011 International Conference on Electric and Electronics (EEIC 2011) in Nanchang, China on June 20-22, 2011, Volume 2 PDF
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Extra resources for Electrical Engineering and Control: Selected Papers from the 2011 International Conference on Electric and Electronics (EEIC 2011) in Nanchang, China on June 20-22, 2011, Volume 2
Keywords: Particle Swarm Optimization; Fuzzy Control Systems; Embedded Mobile Robots. 1 Introduction In the last few years, the improvement of computer engineering and image processing devices were rapidly developed in several applications. , are widely applied in human life applications Especially, the embedded image mobile robot systems are usually developed by the embeddedcomputer, vision-sensors, mechanism and other electrical elements. In real practical engineering, the developed vision-based mobile robot systems with the identified interesting objects in an unknown environment are successfully applied in several application fields.
Randomly construct the initial system parameters. Step 2) Based on (11)-(12) to determine the appropriate parameters of the fuzzy system by the evolutionary PSO learning formulas. Step 3) Gets the fitness value for each individual particle according to the evaluated fitness function by (13). Step 4) Compare each individual’s evaluation fitness value with the personal best value (Pbest) to replace the new Pbest. The best evaluation value among the Pbest is setting to Gbest. Step 5) g=g+1. Step 6) If g=G, then go to exit, otherwise go to step 2.
The Inverse S-transform in Filter with Time-frequency localization. IEEE Transactions on Signal Processing 53(11), 4417–4422 (2005) 9. : S-transform-based Intelligent System for Classification of Power Quality Disturbance Signals. IEEE Transactions on Industrial Electronics 50(4), 800–805 (2003) 10. : Coherency Calculations in the Presence of Structural Dip. In: 67th Annual International Meeting Society of Exploration Geophysicists, Expanded Abstracts, pp. cn Abstract. In this paper, the impact factors of in-degree and out-degree are introduced into community detection, and the directed weighted degree is used to measure the importance of the node.