This article puts forward a model of Mutative Scale Chaos Genetic Algorithm. Using this model to guide the colony to evolve can improve the capability of Genetic Algorithm without changing the searching mechanism of i...
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This article puts forward a model of Mutative Scale Chaos Genetic Algorithm. Using this model to guide the colony to evolve can improve the capability of Genetic Algorithm without changing the searching mechanism of it It is applied to optimize BP network weights and threshold value. The simulative result has proved well that this method is simple, quick and easy to program. It has the quicker astringency speed and less calculation than the old algorithm, and is an effective means of optimizing the neural network weights and threshold value.
Based on the cubic B-spline curve, new Chinese fonts are generated by wavelet transforms in this paper. The outlines of Chinese fonts are first transformed into B-spline curves. Then, using wavelet transforms, the con...
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Based on the cubic B-spline curve, new Chinese fonts are generated by wavelet transforms in this paper. The outlines of Chinese fonts are first transformed into B-spline curves. Then, using wavelet transforms, the control points of each curve are decomposed into hierarchies containing the detailed features of the Chinese fonts. Using the synthesis procedure of wavelet transforms, new fonts can be generated by modifying details at selected hierarchies.
A quadrature rule for the finite Hilbert Transform via trapezoid type inequalities is obtained. Some numerical experiments for different divisions of the interval [a, b] are also presented.
A quadrature rule for the finite Hilbert Transform via trapezoid type inequalities is obtained. Some numerical experiments for different divisions of the interval [a, b] are also presented.
A measure of success for any learning algorithm is how useful it is in a variety of learning situations. Those learning algorithms that support universal function approximation can theoretically be applied to a very l...
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A measure of success for any learning algorithm is how useful it is in a variety of learning situations. Those learning algorithms that support universal function approximation can theoretically be applied to a very large and interesting class of learning problems. Many kinds of neural network architectures have already been shown to support universal approximation. In this paper, we will provide a proof to show that Fuzzy ART augmented with a single layer of perceptrons is a universal approximator. Moreover, the Fuzzy ARTMAP neural network architecture, by itself, will be shown to be a universal approximator.
This paper proposes a stochastic approach to estimate the occlusion and disparity fields of stereoscopic images. The fields are estimated by the Bayesian maximum a posteriori (MAP) framework and Markov random field (M...
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This paper proposes a stochastic approach to estimate the occlusion and disparity fields of stereoscopic images. The fields are estimated by the Bayesian maximum a posteriori (MAP) framework and Markov random field (MRF) models. The occlusion field model is based on the stochastic observation that the probability distribution in MAP estimator is relatively unstable and uniform at occluded regions. The occlusion is explicitly modelled as MRF, and is estimated in an energy optimization method called stochastic diffusion. The detected occluded region is compensated for the re-estimated disparity field in the same stochastic diffusion and the dynamic programming approach. Experimental results show good occlusion detection and disparity estimation. These results show the novel stochastic approach is suitable for occlusion detection and disparity estimation.
This paper proposes a Bayesian Maximum A Posteriori (MAP) method to estimate disparity field and to extract objects in the stereoscopic images. The disparity and segmentation fields are modelled as the Markov random f...
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This paper proposes a Bayesian Maximum A Posteriori (MAP) method to estimate disparity field and to extract objects in the stereoscopic images. The disparity and segmentation fields are modelled as the Markov random fields (MRFs), and are estimated by a stochastic approach called stochastic diffusion. The stochastic diffusion is a new energy minimization method to search for the solution fields in the MAP estimation. A clustering method utilizes the disparity field and color information to classify the regions into foreground objects or background. The line field is also included to improve the detection of the object boundaries. According to the some experiments, the proposed approach shows good performances in the foreground objects extraction even in the complex background.
In the near future, wide variety of wireless networks will be merged into the Internet and allow users to continue their application with higher degree of mobility. In such environment, multimedia applications, which ...
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ISBN:
(纸本)1581137680
In the near future, wide variety of wireless networks will be merged into the Internet and allow users to continue their application with higher degree of mobility. In such environment, multimedia applications, which require smooth rate transmission, will become more popular. There are two main reasons that cause difficulties in the smooth transmission of stream media application when a user roams around the wireless mobile networks: 1) packets may get lost due to the re-routing caused by handoffs;2) due to the disparity in the amount of available bandwidth among wireless cells, handoffs may cause congestion. We propose an end-to-end multi-path transmission sch.me that provides a comprehensive solution for the smooth handoffs of stream media. In the proposed sch.me, multiple paths are acquired during the handoff period to reach a single mobile node. Multi-layer encoding technique is applied to make the stream media more adaptive to the heterogeneous network environment with different bandwidths. Protection of more important video layer through duplicated transmission is carefully designed for smooth handoff using multiple paths. The performance of the proposed multi-path handoff sch.me is evaluated and compared with existing sch.mes through extensive simulations. The simulation results show that the proposed sch.me improves the throughput and quality for stream media application during the handoff. Cost of the proposed sch.me is also carefully evaluated in terms of transmission efficiency.
TCP typically offers reasonable end-to-end performance to users regardless of the bandwidth and error characteristics of particular network technology. The robustness of TCP has contributed to its success in the Inter...
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Previous Bayesian document classification has a problem because it does not reflect semantic relation accurately in expressing characteristic of document. In order to resolve this problem, this paper suggests Bayesian...
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ISBN:
(纸本)3540404554
Previous Bayesian document classification has a problem because it does not reflect semantic relation accurately in expressing characteristic of document. In order to resolve this problem, this paper suggests Bayesian document classification method through mining and refining of association word. Apriori algorithm extracts characteristic of test document in form of association words that reflects semantic relation and it mines association words from learning documents. If association word from learning documents is mined only with Apriori algorithm, inappropriate association word is included within them. Accordingly it has disadvantage of lack of accuracy in document classification. In order to complement the disadvantage, we adopt method to refine association words through use of genetic algorithm. Naïve Bayes classifier classifies test documents based on refined association words.
Agent theories and agent programs are two very different styles of specification of agent behavior. The former are declarative in nature, while the latter have an imperative flavor, In this paper, we combine ideas fro...
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ISBN:
(纸本)9781581136838
Agent theories and agent programs are two very different styles of specification of agent behavior. The former are declarative in nature, while the latter have an imperative flavor, In this paper, we combine ideas from both areas, yielding a powerful mode of agent specification that also gives the specifier a good deal of control over the complexity of the specified agent. In particular, we extend Shapiro et al.'s agent theory to handle prioritized goals and then integrate it with the IndiGolog agent programming language. The result is a new IndiGolog construct that transforms a given nondeterministic, concurrent program δ into a new program δ′ that can be described as a rational implementation of the original program, in the sense that δ′ is an implementation of δ, and furthermore, δ′ is the most rational of all implementations of 6 relative to a given set of prioritized goals and the agent's knowledge. With this construct, we can specify an agent that will attempt to achieve as many goals as possible in priority order even if the agent does not know of a plan that is guaranteed to achieve all the goals. In this case, the agent will select a plan that she thinks has the best chance of achieving the goals.
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