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2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718)最新文献

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Unsupervised channel equalization using fuzzy prediction-error filters 使用模糊预测误差滤波器的无监督信道均衡
2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718) Pub Date : 1900-01-01 DOI: 10.1109/NNSP.2003.1318086
R. Ferrari, C. Panazio, R. Attux, C. Cavalcante, L. Castro, F. V. Zuben, J. Romano
{"title":"Unsupervised channel equalization using fuzzy prediction-error filters","authors":"R. Ferrari, C. Panazio, R. Attux, C. Cavalcante, L. Castro, F. V. Zuben, J. Romano","doi":"10.1109/NNSP.2003.1318086","DOIUrl":"https://doi.org/10.1109/NNSP.2003.1318086","url":null,"abstract":"Ee present a new paradigm for unsupervised nonlinear equalization based on prediction-error fuzzy filters. Tests in different linear channel scenarios are carried out in order to assess the performance of the equalizer. The results show that the proposal is solid and may provide a performance close to that of a Bayesian equalizer.","PeriodicalId":315958,"journal":{"name":"2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718)","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":"114266368","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: 13
Cochleotopic/AMtopic (CAM) and Cochleotopic/Spectrotopic (CSM) map based sound sourcce separation using relaxatio oscillatory neurons 利用松弛振荡神经元进行声源分离的耳蜗/AMtopic (CAM)和耳蜗/Spectrotopic (CSM)图谱
2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718) Pub Date : 1900-01-01 DOI: 10.1109/NNSP.2003.1318065
R. Pichevar, J. Rouat
{"title":"Cochleotopic/AMtopic (CAM) and Cochleotopic/Spectrotopic (CSM) map based sound sourcce separation using relaxatio oscillatory neurons","authors":"R. Pichevar, J. Rouat","doi":"10.1109/NNSP.2003.1318065","DOIUrl":"https://doi.org/10.1109/NNSP.2003.1318065","url":null,"abstract":"We use a two-layered unsupervised bio-inspired neural network to segregate sound sources, e.g. double-vowels or vowels intruded by nonstationary noise sources. The network consists of spiking neurons. The spiking neurons in both layers are modeled by relaxation oscillators. The first layer of the network is locally connected, while the second layer is a fully connected network. We show that in order to correctly segregate sound sources, we should either use Cochleotopic/AMtopic map (CAM) or Cochleotopic/Spectrotopic map (CSM) depending on the nature of the intruding sound source.","PeriodicalId":315958,"journal":{"name":"2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718)","volume":"10 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":"122539701","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
Segregation of stop consonants from acoustic interference 停止辅音与声音干扰的分离
2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718) Pub Date : 1900-01-01 DOI: 10.1109/NNSP.2003.1318064
Guoning Hu, Deliang Wang
{"title":"Segregation of stop consonants from acoustic interference","authors":"Guoning Hu, Deliang Wang","doi":"10.1109/NNSP.2003.1318064","DOIUrl":"https://doi.org/10.1109/NNSP.2003.1318064","url":null,"abstract":"Speech segregation from acoustic interference is a very challenging task. Previous systems have dealt with voiced speech with success, but they cannot handle unvoiced speech. We study the segregation of stop consonants, which contain significant unvoiced signals. We propose a novel method that employs onset as a major cue to segregate stop consonants. Our system first detects stops through onset detection and Bayesian classification of acoustic-phonetic features, and then performs grouping based on onset coincidence. The system has been tested and performs well on utterances mixed with various types of interference.","PeriodicalId":315958,"journal":{"name":"2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718)","volume":"131 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":"122766796","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
Surrogate-based test for Granger causality 格兰杰因果关系的代理检验
2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718) Pub Date : 1900-01-01 DOI: 10.1109/NNSP.2003.1318079
T. Gautama, M. Hulle
{"title":"Surrogate-based test for Granger causality","authors":"T. Gautama, M. Hulle","doi":"10.1109/NNSP.2003.1318079","DOIUrl":"https://doi.org/10.1109/NNSP.2003.1318079","url":null,"abstract":"An approach for testing the presence of Granger causality between two time series is proposed. The residue of the destination signal after self-prediction is computed, after which a cross-prediction of the source signal over this residue is examined. In the absence of causality, there should be no cross-predictive power, due to which the performance of the cross-prediction system can be used as an indication of causality. The proposed approach uses the surrogate data method, and implements the self- and cross-prediction systems as feedforward neural networks. It is tested on synthetic examples, and a sensitivity analysis demonstrates the robustness of the approach.","PeriodicalId":315958,"journal":{"name":"2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718)","volume":"8 6 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":"127374574","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
Training convolutional filters for robust face detection 训练卷积滤波器用于鲁棒人脸检测
2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718) Pub Date : 1900-01-01 DOI: 10.1109/NNSP.2003.1318073
M. Delakis, C. Garcia
{"title":"Training convolutional filters for robust face detection","authors":"M. Delakis, C. Garcia","doi":"10.1109/NNSP.2003.1318073","DOIUrl":"https://doi.org/10.1109/NNSP.2003.1318073","url":null,"abstract":"We present a face detection approach based on a convolutional neural architecture, designed to detect and precisely localize highly variable face patterns, in complex real world images. Our system automatically synthesizes simple problem-specific feature extractors from a training set of face and non face patterns, without making any assumptions or using any hand-made design concerning the features to extract or the areas of the face pattern to analyze. Experiments on different difficult test sets have shown that our approach provide superior overall detection results, while being computationally more efficient than most of state-of-the-art approaches that require dense scanning and local preprocessing.","PeriodicalId":315958,"journal":{"name":"2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718)","volume":"162 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":"121612112","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
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