{"title":"Speech enhancement using bionic wavelet transform and adaptive threshold function","authors":"Yang Xi, Liu Bing-wu, Yan Fang","doi":"10.1109/CINC.2010.5643844","DOIUrl":"https://doi.org/10.1109/CINC.2010.5643844","url":null,"abstract":"By the use of the Bionic Wavelet Transform and adaptive threshold function, this paper presents an improved wavelet-based speech enhancement method, Adaptive Bionic Wavelet Speech Enhancement. Due to the integration of human auditory system model into the wavelet transform, the main advantage of the proposed method is that the over thresholding of speech segments which is usually occurred in conventional wavelet-based speech enhancement schemes can be avoided. Then it can track the variation of noisy speech without the estimation of the a priori knowledge of SNR. As a consequence, the enhanced speech quality of the proposed method can be increased substantially from those of conventional approaches.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114966465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Visibility estimated in foggy road traffic based on atmospheric scattering model","authors":"Chen Xianqiao, Y. Xinping, Chu Xiumin","doi":"10.1109/CINC.2010.5643827","DOIUrl":"https://doi.org/10.1109/CINC.2010.5643827","url":null,"abstract":"In road traffic, there exists foggy condition very often. The foggy affects traffic efficiency, even leads to traffic accidents. So it is important to measure the visibility in foggy road traffic.With this problem, two foggy estimated algorithms are proposed in this paper. In first algorithm, two iamges are used to estimate visibility togather with Atmospheric Scattering Model.The two image must be in same scene and different weather condition.The second algrithm is used one foggy image to estimate the visibility. But there are two key points in the scene,and these points have similar illuminate property.Experments show that these algrithms are effective.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":"263 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133665852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Leader and follower: Agents in an Opinion Dynamics and Bounded Confidence model on the stochastic movement world","authors":"Shusong Li, Shiyong Zhang","doi":"10.1109/CINC.2010.5643896","DOIUrl":"https://doi.org/10.1109/CINC.2010.5643896","url":null,"abstract":"We present and analyze a model of Opinion Dynamics and Bounded Confidence on the stochastic movement world. There are two mechanisms for interaction. ‘Eyeshot’ limits the set of neighbors around the agent and ‘Bounded Confidence’ chooses the agents to exchange the opinion in the set. Every time step, agent i looks for the agents in its eyeshot and adjusts their opinion based on the algorithm of Bounded Confidence. When the exchange ends, every agent moves itself in a random direction and waits for the next time step. There are three special agents in the model, infector, extremist and leader. The infector is specified as an agent with large eyeshot and the extremist is the agent with high confidence. The leader possesses both high confidence and large eyeshot. We simulated the opinion formation process using the proposed model, results show the system is more realistic than the classic BC model.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133407345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Fault diagnosis of power electronic based on multi-resolution analysis and support vector machine","authors":"Jianjun Zhao, Xiao-guang Gu, Heng Yu, W. Yan","doi":"10.1109/CINC.2010.5643877","DOIUrl":"https://doi.org/10.1109/CINC.2010.5643877","url":null,"abstract":"The wavelet multi-resolution analysis (MRA) and support vector machine (SVM) are used in the fault diagnosis of power electronic. First, the paper use the wavelet MRA to deal with the characteristics of power electronic fault signal, and then identifies the fault diagnosis by the multi-class fault classifier based on SVM. The simulation results show the correctness and effectiveness of the method.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":"213 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132440326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Application of the self-organizing competition artificial neural network in distribution networks","authors":"Xue Wei","doi":"10.1109/CINC.2010.5643841","DOIUrl":"https://doi.org/10.1109/CINC.2010.5643841","url":null,"abstract":"The reliability indices of distribution network are practically to reflect the structures and operate characteristics of the whole system. If there are many types of distribution networks need to be assessed, it is very difficult and waste to compute reliability indices repeatedly. In this case, it is very useful to define simple indices to determine distribution network reliability, and avoid terrible computation of indices. In this paper, a self-organizing competition ANN classifier was built to estimate load reliability of distribution network, with redefining indices, which combined reliability and topological structure of distribution network, and reflected the load failure rate. It was helpful to improve the efficiency of network reliability analysis.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126823428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Research of DSP file system based on CF card","authors":"Hai-Bing Su, Qin-Zhang Wu, Juan Zhang","doi":"10.1109/CINC.2010.5643887","DOIUrl":"https://doi.org/10.1109/CINC.2010.5643887","url":null,"abstract":"The capacity of Flash on-board is generally small, the data will be lost after SDRAM power-down, and they can not easily transfer the data to a computer. In order to meet with large-capacity storage needs in the image processing system, this paper uses CF card as removable storage media. It mainly introduces the working principle of CF (Compact Flash) cards and the principle of FAT16 file system, achieves the hardware and software design of the DSP and the CF card interface circuit, compile underlying drive of the CF card and FAT16 file system.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123466590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The central china technical innovation research based on diffusion theory","authors":"Xuetao Sun, S. Huang, X. Peng, Zhiyuan Wang","doi":"10.1109/CINC.2010.5643903","DOIUrl":"https://doi.org/10.1109/CINC.2010.5643903","url":null,"abstract":"Intellectual property rights (IPRs) sharing and communication are the key impetus factor of the central china innovation and practice. Through the analysis of the influence factor and the question of the technological innovation are in the central china, from the aspect of strategic instruction, the policy support and the technical diffusion system construction, we carry on the innovation analysis in the middle area, use the Fick's law to carry on the research of IPRs diffusion mechanism and pattern, and construct the central china innovation policy and way in the innovation condition and the diffusion mechanism foundation.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126270618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Road pavement performance evaluation model based on hybrid genetic algorithm neural network","authors":"Wei-dong Qian","doi":"10.1109/CINC.2010.5643855","DOIUrl":"https://doi.org/10.1109/CINC.2010.5643855","url":null,"abstract":"Road pavement perfoemance evaluation and prediction is two most important parts of pavement management system. In order to scientifically and accurately predict the future road pavement situation,evaluation indexes and main influence factors of pavement performance were analyzed. Then functional performance,structure performance, safety performance, and comfortability performance was selected as the evolution index and three factors were taken as parameters, including temperature, annual precipitation,annual average daily traffic. The two prediction models of BP neural network and hybrid algorithms based on neural network and genetic algorithm were built respectively. Forecasting result shows that neural network model based on genetic algorithms has higher prediction accuracy and more network generalization than those of BP neural network;","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127663151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Study on energy output characteristics calculation method of two charges' shock wave from underwater explosion","authors":"Jun-bo Hu, Qing-min Li, Zhihua Zhang","doi":"10.1109/CINC.2010.5643863","DOIUrl":"https://doi.org/10.1109/CINC.2010.5643863","url":null,"abstract":"Multi-charges exploded synchronously are very useful to improve explosion power. But, there is few of information concerning the peak pressure calculation of two charges' shock wave in present research. The calculation method based on distribution of emitted energy proposed in this paper, considered that under the influence of first charge's emitted energy, the second charge's propagation is changed. Then the correctness of the method has been proved through a series of experiments. Finally, the second charge's peak pressure and its change in entire plane are proposed. This method provides reference information for underwater explosion implement of multi-charges.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":"32 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120979119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Flow shop scheduling problem using hybrid quantum particle swarm optimization algorithm(HQPSO)","authors":"Qunxian Chen","doi":"10.1109/CINC.2010.5643845","DOIUrl":"https://doi.org/10.1109/CINC.2010.5643845","url":null,"abstract":"The flow shop scheduling problem is a combinatorial optimization problem known to be NP-hard, which has captured the interest of a great number of researchers. Many different methods have been applied to solve FSSP and have obtained effective results, but these methods are not satisfying. Based on the quantum theory and particle swarm optimization ,this paper presents an HQPSO algorithm to solve FSSP. Experimental results show that the HQPSO algorithm for FSSP improves the search performance and shows the effectiveness of the algorithm to solve optimization problems..","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123898699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}