We propose an greedy-type adaptive compression numerical algorithm in best m-term approximation. This algorithm provides the asymptotically optimal approximation by tensor product wavelet-type basis for functions from periodic Besov class with mixed smoothness in the Lq norm. Moreover it depends only on the expansion of function f by tensor product wavelet-type basis but neither on q nor on any special features of f.
{"title":"An Greedy-type Algorithm in m-term Approximation For Besov Class with Mixed Smoothness","authors":"Peixin Ye, Qing He","doi":"10.1109/ICNC.2007.200","DOIUrl":"https://doi.org/10.1109/ICNC.2007.200","url":null,"abstract":"We propose an greedy-type adaptive compression numerical algorithm in best m-term approximation. This algorithm provides the asymptotically optimal approximation by tensor product wavelet-type basis for functions from periodic Besov class with mixed smoothness in the Lq norm. Moreover it depends only on the expansion of function f by tensor product wavelet-type basis but neither on q nor on any special features of f.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117092638","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}
A multi-stage objects recognition process based on biomimetic pattern recognition (BPR) and Choquet integral (CI) is proposed to detect and classify the moving objects in video sequence in the intersections. It is difficult to distinguish motorcycle from pedestrians when occlusions happen. In order to solve the problem, BPR is first used to classify the Zernike moments extracted, and CI is then adopted for multi-features fusion based on the output of BPR, the area and the velocity to improve the accuracy. An Experimental example is proposed to test the efficiency of the approach presented.
{"title":"Multi-stage Moving Object Recognition Based on Fuzzy Integral","authors":"Li Wang, Hai-Hong Wang, Xiaoxi Ji","doi":"10.1109/ICNC.2007.488","DOIUrl":"https://doi.org/10.1109/ICNC.2007.488","url":null,"abstract":"A multi-stage objects recognition process based on biomimetic pattern recognition (BPR) and Choquet integral (CI) is proposed to detect and classify the moving objects in video sequence in the intersections. It is difficult to distinguish motorcycle from pedestrians when occlusions happen. In order to solve the problem, BPR is first used to classify the Zernike moments extracted, and CI is then adopted for multi-features fusion based on the output of BPR, the area and the velocity to improve the accuracy. An Experimental example is proposed to test the efficiency of the approach presented.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129582471","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}
In digital wireless communications, blind channel equalization technique plays an important role in combating the intersymbol interference (ISI) caused by nonideal channels or multipath propagation. Convergence behaviors and design cost are two major performance evaluative features. In this paper we present a low complexity blind equalization algorithm suitable for wireless communication channels, by exploiting the signed polarity and improving the iteration version of the super-exponential algorithm for the coefficients adaptation. The proposed algorithm both reduce the computation complexity and ensure a fast speed of convergence with an acceptable steady state compared with conventional one. Computer simulation results are presented to confirm our approach.
{"title":"Optimizing Blind Equalization Intelligent Algorithm for Wireless Communication Systems","authors":"Li-jun Sun, Chaohui Zhao","doi":"10.1109/ICNC.2007.529","DOIUrl":"https://doi.org/10.1109/ICNC.2007.529","url":null,"abstract":"In digital wireless communications, blind channel equalization technique plays an important role in combating the intersymbol interference (ISI) caused by nonideal channels or multipath propagation. Convergence behaviors and design cost are two major performance evaluative features. In this paper we present a low complexity blind equalization algorithm suitable for wireless communication channels, by exploiting the signed polarity and improving the iteration version of the super-exponential algorithm for the coefficients adaptation. The proposed algorithm both reduce the computation complexity and ensure a fast speed of convergence with an acceptable steady state compared with conventional one. Computer simulation results are presented to confirm our approach.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128796110","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}
Imitating such biological immune system mechanisms as self-learning, memory-storing and immune- response, combined with fault tolerance design approach of redundancy and reconfiguration, an immune fault tolerance controller (IFTC) is designed and implemented in the fault tolerance control system of mobile robot. The IFTC can not only retain the good performance under normal operations but also resume desired performance when there are finite failures in system. Robustness and fault tolerance ability of the IFTC are demonstrated by simulation results, and the feasibility and efficiency of above IFTC in fault tolerance control of mobile robot are confirmed. The IFTC presented in this paper can also be applied to the design of fault tolerance control system for other electro-mechanical products.
{"title":"Research on Fault-Tolerant Controller for Mobile Robot Based on Artificial Immune Principle","authors":"Bobo Yang, Shouwen Fan, Mingquan Shi","doi":"10.1109/ICNC.2007.622","DOIUrl":"https://doi.org/10.1109/ICNC.2007.622","url":null,"abstract":"Imitating such biological immune system mechanisms as self-learning, memory-storing and immune- response, combined with fault tolerance design approach of redundancy and reconfiguration, an immune fault tolerance controller (IFTC) is designed and implemented in the fault tolerance control system of mobile robot. The IFTC can not only retain the good performance under normal operations but also resume desired performance when there are finite failures in system. Robustness and fault tolerance ability of the IFTC are demonstrated by simulation results, and the feasibility and efficiency of above IFTC in fault tolerance control of mobile robot are confirmed. The IFTC presented in this paper can also be applied to the design of fault tolerance control system for other electro-mechanical products.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128348972","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}
In this paper, CCD cameras are calibrated implicitly using BP neural network by means of its ability to fit the complicated nonlinear mapping relation. Dense sample data is acquired by using high precisely numerical control platform, and the variances error (PVE) is adopted during training the neural network. The error percentages obtained from our set-up are limitedly better than those obtained through mean square error (MSE). The system is generalization enough for most machine-vision applications and the calibrated system can reach acceptable precision of 3D measurement standard. It is expected that, with this approach, we can maintain the major advantage of linear methods and obtain improved accuracy without any complicated mathematical modeling process thank to nonlinear learning capability of neural networks. The value p needs to be decided by experiments, and the reconstruction images will be distorted if the value is more than 6.
{"title":"Analyzing and Improving of Neural Networks used in Stereo Calibration","authors":"Y. Xing, Jing Sun, Zhentong Chen","doi":"10.1109/ICNC.2007.240","DOIUrl":"https://doi.org/10.1109/ICNC.2007.240","url":null,"abstract":"In this paper, CCD cameras are calibrated implicitly using BP neural network by means of its ability to fit the complicated nonlinear mapping relation. Dense sample data is acquired by using high precisely numerical control platform, and the variances error (PVE) is adopted during training the neural network. The error percentages obtained from our set-up are limitedly better than those obtained through mean square error (MSE). The system is generalization enough for most machine-vision applications and the calibrated system can reach acceptable precision of 3D measurement standard. It is expected that, with this approach, we can maintain the major advantage of linear methods and obtain improved accuracy without any complicated mathematical modeling process thank to nonlinear learning capability of neural networks. The value p needs to be decided by experiments, and the reconstruction images will be distorted if the value is more than 6.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129087583","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}
Visual perception of rotation is one of important functions of processing information in the visual pathway. To simulate the mechanism, we propose a model for perception of rotation. First, we briefly introduce the rotation-invariant basis functions learned from natural scenes using independent component analysis (ICA). We used these basis functions to construct the perceptual model. By using the correlation coefficients of two neural responses as the measure of rotation-invariance, our model can perform the task of perception of rotating angles. Computer simulation results show that the present model is able to perceive rotation- invariance and successfully perceive the relative angles of rotating patches.
{"title":"Computational Model for Rotation-Invariant Perception","authors":"Wenlu Yang, Liqing Zhang, Libo Ma","doi":"10.1109/ICNC.2007.311","DOIUrl":"https://doi.org/10.1109/ICNC.2007.311","url":null,"abstract":"Visual perception of rotation is one of important functions of processing information in the visual pathway. To simulate the mechanism, we propose a model for perception of rotation. First, we briefly introduce the rotation-invariant basis functions learned from natural scenes using independent component analysis (ICA). We used these basis functions to construct the perceptual model. By using the correlation coefficients of two neural responses as the measure of rotation-invariance, our model can perform the task of perception of rotating angles. Computer simulation results show that the present model is able to perceive rotation- invariance and successfully perceive the relative angles of rotating patches.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129736688","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}
Coalition is an important cooperative method in multi-agent system (MAS). It is a complicated combinatorial optimization problem to search for the optimal, task-oriented Agent coalition. A greedy algorithm is presented since no greedy algorithms have been adopted in this problem so far. The greedy criterion is that the more ability and the less cost brought to a coalition by an agent, the better the agent is. Two expressions of the greedy criterion have been studied. The results of contrastive experiments show that this algorithm is effective.
{"title":"Greedy Algorithm Solution to Agent Coalition for Single Task","authors":"Jianguo Jiang, Yong Li, N. Xia","doi":"10.1109/ICNC.2007.409","DOIUrl":"https://doi.org/10.1109/ICNC.2007.409","url":null,"abstract":"Coalition is an important cooperative method in multi-agent system (MAS). It is a complicated combinatorial optimization problem to search for the optimal, task-oriented Agent coalition. A greedy algorithm is presented since no greedy algorithms have been adopted in this problem so far. The greedy criterion is that the more ability and the less cost brought to a coalition by an agent, the better the agent is. Two expressions of the greedy criterion have been studied. The results of contrastive experiments show that this algorithm is effective.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129795099","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}
A novel text independent speaker identification system is proposed. In the proposed system, the 12-order perceptual linear predictive cepstrum and their delta coefficients in the span of five frames are extracted from segmented speech based on the method of pitch synchronous analysis. The Fisher ratio is used to evaluate the effectiveness of speech feature and select the part dimensions of the original 25-dimensional feature vector to form the new 13-dimensional feature vector. The Gaussian mixture model is applied to model the speakers. The experimental results show that the proposed system gives very good performances, which the identification accuracy is significantly better than that of the other 13-dimensional feature based systems and is a little bit better than or just the same as the 25-dimensional feature based system, but the algorithm complexity is much less than that of the 25-dimensional features based system.
{"title":"Pitch Synchronous Analysis Method and Fisher Criterion Based Speaker Identification","authors":"Yumin Zeng, Huayu Wu, Rongchun Gao","doi":"10.1109/ICNC.2007.555","DOIUrl":"https://doi.org/10.1109/ICNC.2007.555","url":null,"abstract":"A novel text independent speaker identification system is proposed. In the proposed system, the 12-order perceptual linear predictive cepstrum and their delta coefficients in the span of five frames are extracted from segmented speech based on the method of pitch synchronous analysis. The Fisher ratio is used to evaluate the effectiveness of speech feature and select the part dimensions of the original 25-dimensional feature vector to form the new 13-dimensional feature vector. The Gaussian mixture model is applied to model the speakers. The experimental results show that the proposed system gives very good performances, which the identification accuracy is significantly better than that of the other 13-dimensional feature based systems and is a little bit better than or just the same as the 25-dimensional feature based system, but the algorithm complexity is much less than that of the 25-dimensional features based system.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129890474","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}
Qiuwen Zhang, Cheng Wang, Zhong Liu, F. Shinohara, T. Yamaoka
With the meteorological factors extracted from EOS/MODIS satellite remotely sensed imagery and the corresponding observed precipitation being the input layer and output layer respectively, a back propagation(BP) artificial neural network(ANN) is learned and trained. As the test and application, the distributed precipitations in Qingjiang river basin located in central China are estimated. It is concluded that the precipitations estimated by the BP ANN based on EOS/MODIS are nearly equal to the observed ones at the rainfall stations distributed in the river basin. It is revealed that the integration of EOS/MODIS and ANN provides a new effective way to estimate the distributed precipitation in river basin.
{"title":"Application of Artificial Neural Network to Distributed Precipitation Estimation Based on EOS/MODIS Remotely Sensed Imagery","authors":"Qiuwen Zhang, Cheng Wang, Zhong Liu, F. Shinohara, T. Yamaoka","doi":"10.1109/ICNC.2007.247","DOIUrl":"https://doi.org/10.1109/ICNC.2007.247","url":null,"abstract":"With the meteorological factors extracted from EOS/MODIS satellite remotely sensed imagery and the corresponding observed precipitation being the input layer and output layer respectively, a back propagation(BP) artificial neural network(ANN) is learned and trained. As the test and application, the distributed precipitations in Qingjiang river basin located in central China are estimated. It is concluded that the precipitations estimated by the BP ANN based on EOS/MODIS are nearly equal to the observed ones at the rainfall stations distributed in the river basin. It is revealed that the integration of EOS/MODIS and ANN provides a new effective way to estimate the distributed precipitation in river basin.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129901779","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}
Moving object detection is currently one of the most active research topics in the domain of computer vision and video processing. In this paper, a simply and fast quadric binarization method is proposed to remove environmental noise points effectively. Moreover, based on the stability of drawing the contour from fixed scene, the background subtraction method is combined with the time-stepping method, an effective method which could be used to detect the movement areas. Through the average weighted of two means can realize to enhance the accuracy in distinguishing target. Experiment results have shown that this method gives stable performances and good robustness.
{"title":"The Precise Recognition of Moving Object in Complex Background","authors":"Weiyao Huang, Zhijing Liu, Wenjuan Pan","doi":"10.1109/ICNC.2007.732","DOIUrl":"https://doi.org/10.1109/ICNC.2007.732","url":null,"abstract":"Moving object detection is currently one of the most active research topics in the domain of computer vision and video processing. In this paper, a simply and fast quadric binarization method is proposed to remove environmental noise points effectively. Moreover, based on the stability of drawing the contour from fixed scene, the background subtraction method is combined with the time-stepping method, an effective method which could be used to detect the movement areas. Through the average weighted of two means can realize to enhance the accuracy in distinguishing target. Experiment results have shown that this method gives stable performances and good robustness.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130370747","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}
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