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International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003最新文献

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Multipopulation genetic programming for forecasting crop pests 作物病虫害预测的多种群遗传规划
International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003 Pub Date : 2004-04-05 DOI: 10.1109/ICNNSP.2003.1279333
Lijue Tang, Miao Li, Jian Zhang
{"title":"Multipopulation genetic programming for forecasting crop pests","authors":"Lijue Tang, Miao Li, Jian Zhang","doi":"10.1109/ICNNSP.2003.1279333","DOIUrl":"https://doi.org/10.1109/ICNNSP.2003.1279333","url":null,"abstract":"This contribution attempts to study on forecasting crop pests with multipopulation genetic programming (MGP). In our previous work, standard genetic programming (SGP) evolves a single population, which often results in premature convergence. This paper concentrates on multipopulation evolution in order to maintain population diversity to avoid this. Comparison between single and multi population shows superiority of the latter. Study of migration interval and migration rate draws the conclusion that it is helpful to obtain optimal solutions that subpopulations keep communicating often and only a few of individuals migrate when communicating. All experiments are based on forecasting wheat stripe rust disease. MGP shows good prediction, which is hopeful to become an auxiliary method for forecasting crop pests.","PeriodicalId":336216,"journal":{"name":"International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132485003","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}
引用次数: 3
HMM based recognition of Chinese tones in continuous speech 基于HMM的汉语连续语音声调识别
International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003 Pub Date : 2004-04-05 DOI: 10.1109/ICNNSP.2003.1280749
Cheng Minli, Chen Xinmin, Zhao Li
{"title":"HMM based recognition of Chinese tones in continuous speech","authors":"Cheng Minli, Chen Xinmin, Zhao Li","doi":"10.1109/ICNNSP.2003.1280749","DOIUrl":"https://doi.org/10.1109/ICNNSP.2003.1280749","url":null,"abstract":"A novel method for recognizing Chinese tones in continuous speech is proposed in this paper. The first and second order differentials of the fundamental frequency logarithmically converted are used as feature parameters. A left-to-right Hidden Markov Modeling with five states, each of which is modeled by a single Gaussian, expresses each of Chinese tones. Non-voiced portions are coded by random values normally distributed to uniformly deal with all the time frames in an utterance. Speaker dependent tone recognition was conducted for ten speakers. The average rate of 81.8% was obtained for these speakers.","PeriodicalId":336216,"journal":{"name":"International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114158976","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}
引用次数: 2
Deploy a secure public wireless network 部署安全的公共无线网络
International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003 Pub Date : 2004-04-05 DOI: 10.1109/ICNNSP.2003.1281211
Hou Fenfei
{"title":"Deploy a secure public wireless network","authors":"Hou Fenfei","doi":"10.1109/ICNNSP.2003.1281211","DOIUrl":"https://doi.org/10.1109/ICNNSP.2003.1281211","url":null,"abstract":"This paper presents a twofold view of public-wide wireless networks: Users and network managers. Providing an easy network experience to the user while keeping the wireless network secure and manageable is a key issue. This paper presents the description of the vendor-independent approach to a secure public wireless local area network being implemented on this university campus. User configuration is kept simple and preliminary usage patterns are shown.","PeriodicalId":336216,"journal":{"name":"International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114146762","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}
引用次数: 0
Optimum nonuniform transmultiplexer design 最佳非均匀多路复用器设计
International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003 Pub Date : 2004-04-05 DOI: 10.1109/ICNNSP.2003.1279381
C.Y.-F. Ho, B. Ling, Y. Liu, P. Tam, K. Teo
{"title":"Optimum nonuniform transmultiplexer design","authors":"C.Y.-F. Ho, B. Ling, Y. Liu, P. Tam, K. Teo","doi":"10.1109/ICNNSP.2003.1279381","DOIUrl":"https://doi.org/10.1109/ICNNSP.2003.1279381","url":null,"abstract":"This paper considers an optimum nonuniform FIR transmultiplexer design subject to specifications in the frequency domain. Our objective is to minimize the sum of the ripple energy for all the individual filters, subject to the specifications on amplitude and aliasing distortions, and to the passband and stopband specifications for the individual filters. This optimum nonuniform transmultiplexer design problem can be formulated as a quadratic semi-infinite programming problem. The dual parametrization algorithm is extended to the design of this nonuniform transmultiplexer problem. If the lengths of the filters are sufficiently long and the set of decimation integers is compatible, then our algorithm guarantees that the solution obtained will give rise to the global minimum, and the required specifications are satisfied.","PeriodicalId":336216,"journal":{"name":"International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129511325","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}
引用次数: 1
Methods for the blind signal separation problem 盲信号分离问题的解决方法
International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003 Pub Date : 2004-04-05 DOI: 10.1109/ICNNSP.2003.1281131
Yan Li, P. Wen, D. Powers
{"title":"Methods for the blind signal separation problem","authors":"Yan Li, P. Wen, D. Powers","doi":"10.1109/ICNNSP.2003.1281131","DOIUrl":"https://doi.org/10.1109/ICNNSP.2003.1281131","url":null,"abstract":"This paper classifies and reviews the available algorithms to blind signal separation (BSS) problem. Based on the separation criteria, we broadly divide all the reviewed algorithms into four categories, namely: classical adaptive, higher-order statistics based, information theory based algorithms and others. For algorithms which might fall into more than one category, categorizing is made according to their main features. Most of the algorithms reviewed in this paper are benchmarks in BSS area. Many BSS algorithms use neural networks to perform the learning rules, probably because neural networks are powerful in nonlinear mapping and learning ability.","PeriodicalId":336216,"journal":{"name":"International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124398489","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}
引用次数: 10
Modeling random gyro drift by time series neural networks and by traditional method 利用时间序列神经网络和传统方法对陀螺随机漂移进行建模
International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003 Pub Date : 2004-04-05 DOI: 10.1109/ICNNSP.2003.1279399
Chen Xiyuan
{"title":"Modeling random gyro drift by time series neural networks and by traditional method","authors":"Chen Xiyuan","doi":"10.1109/ICNNSP.2003.1279399","DOIUrl":"https://doi.org/10.1109/ICNNSP.2003.1279399","url":null,"abstract":"This paper presents modeling random gyro drift rate by traditional time series method , and makes compensation for gyro drift by Kalman filter, and proposes the modeling and forecasting method by neural networks for strapdown gyro based on time series analysis, and makes a research for random drift rate of gyro applied for strapdown inertial navigation systems, comparison between the results of by Kalman filter based traditional time series method and by time series neural networks is presented.","PeriodicalId":336216,"journal":{"name":"International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117217738","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}
引用次数: 37
Estimation of Bayesian network algorithm with GA searching for better network structure 贝叶斯网络估计算法结合遗传算法搜索更好的网络结构
International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003 Pub Date : 2003-12-01 DOI: 10.1109/ICNNSP.2003.1279302
H. Handa, O. Katai
{"title":"Estimation of Bayesian network algorithm with GA searching for better network structure","authors":"H. Handa, O. Katai","doi":"10.1109/ICNNSP.2003.1279302","DOIUrl":"https://doi.org/10.1109/ICNNSP.2003.1279302","url":null,"abstract":"Estimation of Bayesian network algorithms, which adopt Bayesian networks as the probabilistic model were one of the most sophisticated algorithms in the estimation of distribution algorithms. However the estimation of Bayesian network is key topic of this algorithm, conventional EBNAs adopt greedy searches to search for better network structures. In this paper, we propose a new EBNA, which adopts genetic algorithm to search the structure of Bayesian network. In order to reduce the computational complexity of estimating better network structures, we elaborates the fitness function of the GA module, based upon the synchronicity of specific pattern in the selected individuals. Several computational simulations on multidimensional knapsack problems show us the effectiveness of the proposed method.","PeriodicalId":336216,"journal":{"name":"International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114815205","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}
引用次数: 10
Enhancement of wavelet-coded images via novel directional filtering 基于新方向滤波的小波编码图像增强
International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003 Pub Date : 2003-12-01 DOI: 10.1109/ICNNSP.2003.1281052
Seungjong Kim, Jechang Jeong
{"title":"Enhancement of wavelet-coded images via novel directional filtering","authors":"Seungjong Kim, Jechang Jeong","doi":"10.1109/ICNNSP.2003.1281052","DOIUrl":"https://doi.org/10.1109/ICNNSP.2003.1281052","url":null,"abstract":"In many multimedia applications image compression is required to substantially reduce the amount of image data. This compression, however, sometimes brings artifacts. Typical artifacts are blocking artifacts and mosquito noise in DCT-coded images, and ringing artifacts around edges in wavelet-coded images. We propose a new directional post-processing algorithm which can reduce ringing artifacts around edges of a compressed image. The algorithm detects edge direction in each N/spl times/N block and then applies an appropriate window shape to decoded N/spl times/N block images for nonlinear filtering. Simulation results show that the proposed algorithm is as effective as or more effective than existing nonlinear filtering techniques.","PeriodicalId":336216,"journal":{"name":"International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116049710","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}
引用次数: 3
Automatic segmentation of Chinese chunks using a neural network 基于神经网络的中文块自动切分
International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003 Pub Date : 2003-12-01 DOI: 10.1109/ICNNSP.2003.1279221
Rong-bo Wang, Z. Chi
{"title":"Automatic segmentation of Chinese chunks using a neural network","authors":"Rong-bo Wang, Z. Chi","doi":"10.1109/ICNNSP.2003.1279221","DOIUrl":"https://doi.org/10.1109/ICNNSP.2003.1279221","url":null,"abstract":"Chunk analysis method is a new idea proposed in recent years in developing new machine translation methods. Chinese chunk analysis plays a very important role in machine translation from Chinese to foreign languages. The automatic segmentation of Chinese chunks is the basis of Chinese chunk analysis. It is important for processing real text and corpus construction. This paper presents a method for automatic segmentation of Chinese chunks based on 3-layers neural networks. The corpus we used has been processed with Chinese word segmentation and phrase identification and tagging. In the neural networks model, the input data is the segmentation situation of every character and its combinations with neighbor characters in a Chinese sentence. The output is the segmentation results of every character in a Chinese sentence. The preliminary results show that the method is feasible and effective.","PeriodicalId":336216,"journal":{"name":"International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126663820","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}
引用次数: 2
Region-based binary tree representation for image classification 基于区域的二叉树图像分类
International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003 Pub Date : 2003-12-01 DOI: 10.1109/ICNNSP.2003.1279254
Zhiyong Wang, D. Feng, Z. Chi
{"title":"Region-based binary tree representation for image classification","authors":"Zhiyong Wang, D. Feng, Z. Chi","doi":"10.1109/ICNNSP.2003.1279254","DOIUrl":"https://doi.org/10.1109/ICNNSP.2003.1279254","url":null,"abstract":"Image classification is a very challenging problem due to lack of effective representations. In this paper, a region-based binary tree representation incorporating with adaptive processing of data structures is proposed to address this problem. After an image is segmented, a binary tree is established to characterize its contents by using region merging method. Finally, an adaptive processing of data structure algorithm is employed to perform the classification task with binary tree representation. Experimental results on seven categories of scenery images show this region-based structural representation is superior to our previous work based on quadtree representation.","PeriodicalId":336216,"journal":{"name":"International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115380268","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}
引用次数: 8
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