This research presents the mathematical model to roam an autonomous vehicle in a closed region with minor coincident areas. This model is blind algorithm, no literature that concern on mathematical model. It is essent...
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ISBN:
(纸本)9781665454803
This research presents the mathematical model to roam an autonomous vehicle in a closed region with minor coincident areas. This model is blind algorithm, no literature that concern on mathematical model. It is essential for agricultural technology, for example, shoveling soil for planting, spraying liquid fertilizer, harvesting agricultural products, to control the movement of the vehicle with the redundant path is as less as possible is benefited to decrease the working hours and also the burning oil and more for cost-saving without any expensive hardware. The almost wholly filled farmland depends on the shape, the size of the area, and the vehicle dimension.
As a way to realize an adaptive array of small size, low cost, and low power consumption, there exists a configuration method combining analog signal processing and digital signal processing. M-CMA has been proposed a...
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As a way to realize an adaptive array of small size, low cost, and low power consumption, there exists a configuration method combining analog signal processing and digital signal processing. M-CMA has been proposed as a control algorithm for such an approach. However, when this approach is applied to an actual communication system, there arises the problem that the narrow-band filter in the receiver prevents M-CMA from converging to the desired solution. In this paper, in order to effectively operate an M-CMA adaptive array in the presence of a narrow-band filter, a configuration is proposed in which polyphase filters are used as narrow-band filters. Its superior interference suppression capability is confirmed by a theoretical analysis and computer simulation. (C) 2002 Wiley Periodicals, Inc.
A major problem with blind equalization algorithms based on the distribution matching principle is that they need a long time to accomplish their convergence. What affects convergence has not been discovered to date. ...
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A major problem with blind equalization algorithms based on the distribution matching principle is that they need a long time to accomplish their convergence. What affects convergence has not been discovered to date. The similarity between the least mean-square (LMS) algorithm (widely used for adaptive equalization) and the blind algorithms is considered here. It is expected that the convergence of the blind algorithms is dependent on the condition number of the correlation matrix of the input sequence. Prefiltering methods, including coefficient-fixed type and coefficient-adaptive type, are derived for blind equalization. In these methods, the prefilters are realized by a prediction error filter, which has the ability to compensate for amplitude distortion induced by a channel. Since the prefilters have such ability, the blind equalizers to be cascaded with them are required only to compensate for phase distortion. As a result, the burden imposed on the blind equalizers is reduced. The prefilters output a near-white sequence and lead to an improvement in the convergence of the blind algorithms, being degraded as the condition number is increased. The effectiveness of the proposed methods is validated by computer simulations.
We propose a new feature-based algorithm to detect image splicings without any prior information. Local features are computed from the co-occurrence of image residuals and used to extract synthetic feature parameters....
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ISBN:
(纸本)9781467368032
We propose a new feature-based algorithm to detect image splicings without any prior information. Local features are computed from the co-occurrence of image residuals and used to extract synthetic feature parameters. Splicing and host images are assumed to be characterized by different parameters. These are learned by the image itself through the expectation-maximization algorithm together with the segmentation in genuine and spliced parts. A supervised version of the algorithm is also proposed. Preliminary results on a wide range of test images are very en-couraging, showing that a limited-size, but meaningful, learning set may be sufficient for reliable splicing localization.
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