With the developing of low-power wireless techniques such as the micro-sensors, analog and digital electronic technology and radio frequency technology, different kinds of wireless sensor networks are widely used in t...
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With the developing of low-power wireless techniques such as the micro-sensors, analog and digital electronic technology and radio frequency technology, different kinds of wireless sensor networks are widely used in the field of military, civil, medical and so on. However, in practical applications, the low-power consumption and long-distance have not been well achieved in the wireless sensor networks. In this paper, a low-power and long-distance system based on wireless sensor networks is proposed. The system model consists of two parts: the hardware includes server node, client nodes and ARM boards. The software mainly handle the analysis and construction of the communication frame as well as data analysis and processing and then the data information is processed to report to the server. We can reduce the energy consumption and increase the transmission distance by the combined application of hardware and software. The system can be used in different occasions and does have a grand application prospect.
Locally linear embedding(LLE)algorithm has a distinct deficiency in practical *** requires users to select the neighborhood parameter,k,which denotes the number of nearest neighbors.A new adaptive method is presented ...
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Locally linear embedding(LLE)algorithm has a distinct deficiency in practical *** requires users to select the neighborhood parameter,k,which denotes the number of nearest neighbors.A new adaptive method is presented based on supervised LLE in this article.A similarity measure is formed by utilizing the Fisher projection distance,and then it is used as a threshold to select *** samples will produce different k adaptively according to the density of the data *** method is applied to classify plant *** experimental results show that the average classification rate of this new method is up to 92.4%,which is much better than the results from the traditional LLE and supervised LLE.
In the real word, the complex problems usually have netted structure, namely netted problems. The general methods to solve this kind of problems are based on the sequence structural description or tree structural desc...
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In this paper, a discrete time model of the mixed TCP and UDP connection with the RED is introduced. We use this one order discrete-time model to explain the instability, bifurcation and chaotic behaviors of the syste...
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Video summarization provides condensed and succinct representations of the content of a video stream. A static storyboard summarization approach based on robust low-rank subspace segmentation is proposed in this paper...
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Shrub encroachment has been a wide phenomenon across the arid and semi-arid grasslands in Inner Mongolia, China. Although numerous studies have investigated the effect of this phenomenon on community composition, ecos...
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Shrub encroachment has been a wide phenomenon across the arid and semi-arid grasslands in Inner Mongolia, China. Although numerous studies have investigated the effect of this phenomenon on community composition, ecosystem structure, and nutrient cycling, reports on the distribution patterns of shrub encroachment are limited. A recent development in satellite remote sensing enables accurate assessment of shrub distribution and its dynamics at large scales. In this paper, the combined ground survey in Xianghuangqi, four satellite images (with spatial resolution of 5.8 m) of ZY-3, covering nearly the whole area and taken between July and August in 2013, were used to identify the shrub distribution in this region. It should be noted that the shrub here indicated the shrub-grass mosaic due to the mixed pixel effect, and the identification was weak when the coverage of shrub was on low levels. The NDVI threshold method was first used to extract the vegetation coverage area, and then three traditional pixel-oriented methods (Support vector machine, Maximum likelihood and Mahalanobis distance), compared with the object-oriented method, were used for the classification of images. Object-oriented method is different from the traditional one, in that the classification is not based on the spectral characteristics of individual pixel, but relies on the image object with spatial texture and shape and size characteristics. Ground survey data were used to compare the accuracy level of these methods. It indicated that the shrub recognition accuracy by using support vector machine algorithm is the highest among the three pixel-oriented methods, with higher producer accuracy and user accuracy than the other two algorithms. Furthermore, the overall classification accuracy of this algorithm is 81.15% higher than that of the maximum likelihood (73.33%) and the Mahalanobis distance (61.77%). However, the overall recognition accuracy by using the object-oriented approach (combined scale
In this study, we are concerned with controlling Hopf bifurcation in a dual model of Internet congestion control algorithms. The stability of this system depends on a communication delay parameter, and Hopf bifurcatio...
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Due to the uncertainty principle, the traditional single window based discrete Gabor transform has a fixed joint time-frequency resolution. In order to improve the joint time-frequency resolution of the traditional di...
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Turbo codes have a wide range of applications in 3G mobile communications, deep-sea communications, satellite communications and other power constrained fields. In the paper, the Turbo Code Decoding Principle and seve...
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Dynamic programming(DP) is not a useful tool for solving many control problems because of its complexity in computation. In this paper,we propose Approximate Dynamic Programming(ADP) optimal control strategy for ship ...
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ISBN:
(纸本)9781479900305
Dynamic programming(DP) is not a useful tool for solving many control problems because of its complexity in computation. In this paper,we propose Approximate Dynamic Programming(ADP) optimal control strategy for ship course trajectory tracking control *** system transformation,we convert the optimal tracking problem into designing a infinite-horizon optimal regulator for the tracking error ***-dependent Heuristic Dynamic programming(ADHDP) technique,as one form of ADR is presented to obtain the infinite-horizon optimal tracking *** the ship course optimal tracking control simulation results,we can see that the ADHDP controller makes the performance index and the control sequence for the error dynamics converge to the optimal *** BP neural networks are used as parametric structures to implement ADHDP *** two neural networks aim at approximating the cost function and the control law,respectively.
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