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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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A preferred link functions for delay-constrained least-cost routing 首选链路用于时延约束下的最小开销路由
International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003 Pub Date : 2003-12-01 DOI: 10.1109/ICNNSP.2003.1281182
Liuqing Chen, Hua-An Zhao
{"title":"A preferred link functions for delay-constrained least-cost routing","authors":"Liuqing Chen, Hua-An Zhao","doi":"10.1109/ICNNSP.2003.1281182","DOIUrl":"https://doi.org/10.1109/ICNNSP.2003.1281182","url":null,"abstract":"This paper presents two new preferred link functions: LBC(low bound on cost) and LBC/sub RDM/ (low bound on cost-residual delay maximum). Based on LBC and LBC/sub RDM/, we propose two algorithms DCLC LBC and DCLC LBCRDM for delay constrained least cost routing. The computation results of random networks show that the performances of DCLC LBC and DCLC LBCRDM are comparable, and they are obviously better than the algorithm DCLC-RDM.","PeriodicalId":336216,"journal":{"name":"International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003","volume":"43 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":"115649834","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
Sampling Gabor features for face recognition 人脸识别的采样Gabor特征
International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003 Pub Date : 2003-12-01 DOI: 10.1109/ICNNSP.2003.1280751
Dang-Hui Liu, K. Lam, Lansun Shen
{"title":"Sampling Gabor features for face recognition","authors":"Dang-Hui Liu, K. Lam, Lansun Shen","doi":"10.1109/ICNNSP.2003.1280751","DOIUrl":"https://doi.org/10.1109/ICNNSP.2003.1280751","url":null,"abstract":"The Gabor feature is effective for facial image representation. However, the dimension of a Gabor feature vector is very high so that the computation and memory requirements are prohibitively large. In this paper, we propose a method to determine the optimal position for extracting the Gabor feature. The sub-sampled positions of the feature points are determined by a mask generated from a set of training images by means of principal component analysis (PCA). With the feature vector of reduced dimension, a subspace LDA is applied for face recognition. Experimental results show that the new sampling method is simple, and effective for both dimension reduction and image representation. The recognition rate based on our proposed scheme is also higher than that achieved using a regular sampling method in a face region.","PeriodicalId":336216,"journal":{"name":"International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003","volume":"44 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":"123351068","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
Automatic digital modulation recognition using artificial neural networks 基于人工神经网络的数字调制自动识别
International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003 Pub Date : 1900-01-01 DOI: 10.1109/ICNNSP.2003.1279260
Zhao Yaqin, Guanghui Ren, Xuexia Wang, W. Zhi-lu, Xuemai Gu
{"title":"Automatic digital modulation recognition using artificial neural networks","authors":"Zhao Yaqin, Guanghui Ren, Xuexia Wang, W. Zhi-lu, Xuemai Gu","doi":"10.1109/ICNNSP.2003.1279260","DOIUrl":"https://doi.org/10.1109/ICNNSP.2003.1279260","url":null,"abstract":"This paper presents a modified structure and learning algorithm of artificial neural networks (ANN) for recognizing baseband signal modulation types in the presence of additive white Gaussian noise. The new method employs a layer with less output nodes and an error back propagation learning algorithm with momentum to improve the recognition performance. Simulation results and performance evaluation of the ANN are given and it is shown that the benefits of the developed method are that its structure is simple and it performs well at low signal to noise ratio (SNR) with high overall success rates.","PeriodicalId":336216,"journal":{"name":"International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115405983","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: 51
Sparse training procedure for kernel neuron 核神经元稀疏训练方法
International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003 Pub Date : 1900-01-01 DOI: 10.1109/ICNNSP.2003.1279210
Jianhua Xu, Xuegong Zhang, Yanda Li
{"title":"Sparse training procedure for kernel neuron","authors":"Jianhua Xu, Xuegong Zhang, Yanda Li","doi":"10.1109/ICNNSP.2003.1279210","DOIUrl":"https://doi.org/10.1109/ICNNSP.2003.1279210","url":null,"abstract":"The kernel neuron is the generalization of classical McCulloch-Pitts neuron using Mercer kernels. In order to control generalization ability and prune structure of kernel neuron, we construct a regularized risk functional including both empirical risk functional and Laplace regularization term in this paper. Based on the gradient descent method, a novel training algorithm is designed, which is referred to as the sparse training procedure for kernel neuron. Such a procedure can realize three main ideas: kernel, regularization (or large margin) and sparseness in the kernel machines (e.g. support vector machines, kernel Fisher discriminant analysis, etc.), and can deal with the nonlinear classification and regression problems effectively.","PeriodicalId":336216,"journal":{"name":"International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121814290","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
An adaptive on-line algorithm for independent component analysis 独立分量分析的自适应在线算法
International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003 Pub Date : 1900-01-01 DOI: 10.1109/ICNNSP.2003.1281119
Xiao-ou Li, Yun Zhou, Huan-qing Feng
{"title":"An adaptive on-line algorithm for independent component analysis","authors":"Xiao-ou Li, Yun Zhou, Huan-qing Feng","doi":"10.1109/ICNNSP.2003.1281119","DOIUrl":"https://doi.org/10.1109/ICNNSP.2003.1281119","url":null,"abstract":"This paper presents an adaptive on-line algorithm whose optimization criterion is based on maximum likelihood to perform Independent Component Analysis (ICA). A fast density estimation method is introduced , it can quickly achieve the true score functions of the unknown sources by estimating from the sample. In the meantime, the careful selection of the step size is often necessary to obtain good performance for the source separation tasks. We carry out the global minimum of the contrast function with the gradient adaptive step size. The results of simulation experiment show that the provided algorithm can perform the adaptive separation of real digital signal efficiently.","PeriodicalId":336216,"journal":{"name":"International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116962993","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
A novel adaptive search strategy of intensification and diversification in tabu search 禁忌搜索中一种增强和多样化的自适应搜索策略
International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003 Pub Date : 1900-01-01 DOI: 10.1109/ICNNSP.2003.1279300
Guangyuan Liu, Yi He, Yonghui Fang, Yuhui Qiu
{"title":"A novel adaptive search strategy of intensification and diversification in tabu search","authors":"Guangyuan Liu, Yi He, Yonghui Fang, Yuhui Qiu","doi":"10.1109/ICNNSP.2003.1279300","DOIUrl":"https://doi.org/10.1109/ICNNSP.2003.1279300","url":null,"abstract":"Intensification and diversification are two highly important components of tabu search. At many cases, these two components are also conflicting between them. It is worthy of being studied that how to harmonize this conflict. Aiming at this problem, a novel adaptive search strategy of intensification and diversification was proposed in this paper. Taking traveling salesman problem as samples, many experiments was investigated. The results shows: this strategy is feasible and effective.","PeriodicalId":336216,"journal":{"name":"International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117223581","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: 18
An efficient VLSI implementation of DWT for JPEG2000 JPEG2000中DWT的高效VLSI实现
International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003 Pub Date : 1900-01-01 DOI: 10.1109/ICNNSP.2003.1281035
Ke Zhu, Xiaofang Zhou, Lin Hua, Qian-ling Zhang
{"title":"An efficient VLSI implementation of DWT for JPEG2000","authors":"Ke Zhu, Xiaofang Zhou, Lin Hua, Qian-ling Zhang","doi":"10.1109/ICNNSP.2003.1281035","DOIUrl":"https://doi.org/10.1109/ICNNSP.2003.1281035","url":null,"abstract":"This paper proposed an efficient VLSI architecture for lifting-based Discrete Wavelet Transformation (DWT) recommended by JPEG2000. The architecture included the basic processing element (PE) and the memory control unit (MCU) and the memory modules. The finite precision analysis has been carried out and the data path width was fixed at 20bis. The memory module included fourteen basic memory units. Ten of them were used to the DWT processing and the residual four units was used to entropy coding. The MCU was in charge of the memory access and set up a pipelining processing between the DWT and entropy coding in JPEG2000. The architecture has default filters to generate an output every cycle for JPEG2000. The architecture has been implemented in behavioral Verilog. The estimated gates of our proposed architecture in SIMC 0.18-/spl mu/m technology are 6600 and the estimated frequency of operation is 300 Mhz.","PeriodicalId":336216,"journal":{"name":"International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003","volume":"127 48","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120820437","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: 4
A new temporal-angular correlative distributed source model 一种新的时角相关分布源模型
International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003 Pub Date : 1900-01-01 DOI: 10.1109/ICNNSP.2003.1281110
W. Xiong, Z. Ye, Qiong Li, Xu Xu
{"title":"A new temporal-angular correlative distributed source model","authors":"W. Xiong, Z. Ye, Qiong Li, Xu Xu","doi":"10.1109/ICNNSP.2003.1281110","DOIUrl":"https://doi.org/10.1109/ICNNSP.2003.1281110","url":null,"abstract":"This paper expands the temporal-angular independent distributed source model to a temporal-angular correlative model by using 1-order AR model and Von Mises angular function. Then it analyses and simulates the new model's Cramer-Rao Bound (CRB). Theoretical analysis and simulations illustrate that the new model is effective.","PeriodicalId":336216,"journal":{"name":"International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121209073","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
Nonextensive entropy analysis of non-stationary ERP signals 非平稳ERP信号的非广泛熵分析
International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003 Pub Date : 1900-01-01 DOI: 10.1109/ICNNSP.2003.1279398
M. Shen, Qianhua Zhang, P. Beadle
{"title":"Nonextensive entropy analysis of non-stationary ERP signals","authors":"M. Shen, Qianhua Zhang, P. Beadle","doi":"10.1109/ICNNSP.2003.1279398","DOIUrl":"https://doi.org/10.1109/ICNNSP.2003.1279398","url":null,"abstract":"The application of a measurement of entropy defined from the nonextensive entropy, the Tsallis-like time-dependent entropy (TDE), is proposed to investigate the event-related potential (ERPs). The TDE carries information about the degree of order or disorder associated with a multi-frequency signal response. The statistical characteristics of the TDE for different signal distributions are studied. TDE was estimated for the ERP signals recorded from several healthy subjects with a specified cognitive task. A significant decrease of entropy was correlated with the responses to target stimulus (P300). The experimental results indicate that the TDE can be employed as a quantitative measurement for monitoring the ERPs activities and other signal processing.","PeriodicalId":336216,"journal":{"name":"International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127317510","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
Improving performance of gene selection by unsupervised learning 利用无监督学习改进基因选择性能
International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003 Pub Date : 1900-01-01 DOI: 10.1109/ICNNSP.2003.1279209
Mingyi Wang, Ping Wu, Shu-Quan Xia
{"title":"Improving performance of gene selection by unsupervised learning","authors":"Mingyi Wang, Ping Wu, Shu-Quan Xia","doi":"10.1109/ICNNSP.2003.1279209","DOIUrl":"https://doi.org/10.1109/ICNNSP.2003.1279209","url":null,"abstract":"Selection of significant genes via expression profiles is an important problem in microarray experiments for diseases classification and prediction. Genes of interest are typically selected by a statistical significance test and the top ranked genes were used. A problem with this approach is that many of these genes are highly correlated. For classification purposes it required to have distinct but still highly informative genes. In this paper, we proposed an unsupervised feature selection algorithm to resolve this problem. The method retrieves groups of similar genes by measuring similarity between them whereby redundancy therein is removed. This does not need any search and therefore, is fast. Real biological data experiments have shown that this approach will significantly improve existing classifiers.","PeriodicalId":336216,"journal":{"name":"International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124777618","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: 4
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