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Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.最新文献

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Indirect field-oriented linear induction motor drive with Petri fuzzy-neural-network control 基于Petri模糊神经网络控制的间接磁场定向线性感应电机驱动
Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005. Pub Date : 2005-12-27 DOI: 10.1109/IJCNN.2005.1555860
R. Wai, Chia-Chin Chu
{"title":"Indirect field-oriented linear induction motor drive with Petri fuzzy-neural-network control","authors":"R. Wai, Chia-Chin Chu","doi":"10.1109/IJCNN.2005.1555860","DOIUrl":"https://doi.org/10.1109/IJCNN.2005.1555860","url":null,"abstract":"This study focuses on the development of a Petri fuzzy-neural-network (PFNN) control for an indirect field-oriented linear induction motor (LIM) drive. The concept of a Petri net (PIN) is incorporated into a traditional fuzzy-neural-network (TFNN) to form a newly-type PFNN framework for alleviating the computation burden. Moreover, the supervised gradient descent method is used to develop the online training algorithm for the PFNN. In order to guarantee the convergence of tracking error, analytical methods based on a discrete-type Lyapunov function are proposed to determine the varied learning rates of the PFNN. With the proposed PFNN control system, the mover position of the controlled LIM drive possesses the advantages of good transient control performance and robustness to uncertainties for the tracking of periodic reference trajectories. In addition, the effectiveness of the proposed control scheme is verified by numerical simulations.","PeriodicalId":365690,"journal":{"name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133790312","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
Speaker identification using speech and lip features 利用言语和嘴唇特征识别说话人
Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005. Pub Date : 2005-12-27 DOI: 10.1109/IJCNN.2005.1556307
Guobin Ou, Xin Li, XiaoCao Yao, HongBin Jia, Y. Murphey
{"title":"Speaker identification using speech and lip features","authors":"Guobin Ou, Xin Li, XiaoCao Yao, HongBin Jia, Y. Murphey","doi":"10.1109/IJCNN.2005.1556307","DOIUrl":"https://doi.org/10.1109/IJCNN.2005.1556307","url":null,"abstract":"We present a speaker identification system that uses synchronized speech signals and lip features. We developed an algorithm that automatically extracts lip areas from speaker images, and a neural network system that integrates the two different types of signals to give accurate identification of speakers. We show that the proposed system gives better performances than the systems that use only speech or lip features in both text dependant and text independent speaker identification applications.","PeriodicalId":365690,"journal":{"name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124419654","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: 5
A recurrent neural network for sound-source motion tracking and prediction 用于声源运动跟踪和预测的递归神经网络
Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005. Pub Date : 2005-12-27 DOI: 10.1109/IJCNN.2005.1556248
J. Murray, H. Erwin, S. Wermter
{"title":"A recurrent neural network for sound-source motion tracking and prediction","authors":"J. Murray, H. Erwin, S. Wermter","doi":"10.1109/IJCNN.2005.1556248","DOIUrl":"https://doi.org/10.1109/IJCNN.2005.1556248","url":null,"abstract":"Recurrent neural networks (RNN) have been used in many applications for both pattern detection and prediction. This paper shows the use of RNN's as a speed classifier and predictor for a robotic sound source tracking system. The system requires extensive training to classify all possible speeds to enable dynamic tracking of the most prominent sound within the environment.","PeriodicalId":365690,"journal":{"name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114486492","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: 5
A new pulse mode self organizing map hardware with digital phase locked loops 一种新型带数字锁相环的脉冲模式自组织地图硬件
Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005. Pub Date : 2005-12-27 DOI: 10.1109/IJCNN.2005.1556378
H. Hikawa
{"title":"A new pulse mode self organizing map hardware with digital phase locked loops","authors":"H. Hikawa","doi":"10.1109/IJCNN.2005.1556378","DOIUrl":"https://doi.org/10.1109/IJCNN.2005.1556378","url":null,"abstract":"The self-organizing map (SOM) has found applicability in a wide range of application areas. This paper proposes a new SOM hardware with phase modulated pulse signal and digital phase-locked loops (DPLLs). The system uses the DPLL as a computing element because the operation of the DPLL is very similar to that of SOM's computation. The system also uses square waveform phase to hold the value of the each input vector element. The proposed SOM architecture is described in VHDL and its feasibility is verified by simulation. Results show that the proposed SOM has good quantization capability.","PeriodicalId":365690,"journal":{"name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114861198","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
Hybrid neural-phenomenological sub-models and its application to Earth-space path signal attenuation prediction 神经-现象学混合子模型及其在地空路径信号衰减预测中的应用
Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005. Pub Date : 2005-12-27 DOI: 10.1109/IJCNN.2005.1556273
L. Calôba, G. A. Alencar, M. S. Assis
{"title":"Hybrid neural-phenomenological sub-models and its application to Earth-space path signal attenuation prediction","authors":"L. Calôba, G. A. Alencar, M. S. Assis","doi":"10.1109/IJCNN.2005.1556273","DOIUrl":"https://doi.org/10.1109/IJCNN.2005.1556273","url":null,"abstract":"Neural models may be very precise but, being numerical, provide only limited contribution to the understanding of the phenomenological process, contrary to phenomenological models. In this paper we use neural techniques to evaluate and to provide information on the sub-models that composes a phenomenological model. We also show how some hybrid neural-phenomenological sub-models may be used to maximally preserve the phenomenological information while providing numerical precision. The problem of radio wave degradation by rain is critical for the design of reliable Earth-satellite communication links operating above 10 GHz. Phenomenological models available in the literature are complex and show poor accuracy, and so are good candidates for the proposed technique. The use of this technique in the UIT-R model presented very interesting results.","PeriodicalId":365690,"journal":{"name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114545178","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
Extraction of frame-difference features based on PCA and ICA for lip-reading 基于PCA和ICA的唇读帧差特征提取
Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005. Pub Date : 2005-12-27 DOI: 10.1109/IJCNN.2005.1555835
K. Lee, M. Lee, Soo-Young Lee
{"title":"Extraction of frame-difference features based on PCA and ICA for lip-reading","authors":"K. Lee, M. Lee, Soo-Young Lee","doi":"10.1109/IJCNN.2005.1555835","DOIUrl":"https://doi.org/10.1109/IJCNN.2005.1555835","url":null,"abstract":"The features of human lip motion from video clips are extracted by principal component analysis (PCA) and independent component analysis (ICA). Unlike many other features extracted from single-frame static images or multi-frame dynamic images, we extracted the features from the differences of consecutive frames. The PCA results in global features, while local features are extracted by the ICA. The features are extracted from several consecutive multi-frame differences as well as single-frame differences. The dynamic nature of multi-frame differences is more eminent. The resulting features maybe applicable in lip-reading and synthesis of lip motion videos with text-to-speech capability.","PeriodicalId":365690,"journal":{"name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114906682","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: 9
A phase-equation model for a large phase lead in manual tracking caused by intermittent visual information 人工跟踪中由于视觉信息间断导致的大相位差的相位方程模型
Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005. Pub Date : 2005-12-27 DOI: 10.1109/IJCNN.2005.1556134
T. Yasuhiro, S. Yasuji
{"title":"A phase-equation model for a large phase lead in manual tracking caused by intermittent visual information","authors":"T. Yasuhiro, S. Yasuji","doi":"10.1109/IJCNN.2005.1556134","DOIUrl":"https://doi.org/10.1109/IJCNN.2005.1556134","url":null,"abstract":"We propose a phase-equation model for a large phase lead in manual tracking with intermittent visual information. We have recently reported that hand motion largely led to the target motion when the target was intermittently displayed with a specific timing (Takachi and Sawada, 2004). To adapt the general tracking model to the intermittent manual tracking, we suppose that the geometric factor coupling with the target velocity is indispensable as a feedforward control, and the feedback control intermittently contributes to the hand motion. Results of simulations show that the large phase lead is due to both the decrease in visual information and the synchronicity between the timing of target display and the effect of the rhythmic hand motion caused by the geometric property of the target path.","PeriodicalId":365690,"journal":{"name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116929089","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
Optimization of parameters for effective Web information retrieval using an evolutionary algorithm 基于进化算法的有效Web信息检索参数优化
Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005. Pub Date : 2005-12-27 DOI: 10.1109/IJCNN.2005.1555896
J. Zakos, Ping Zhang, B. Verma
{"title":"Optimization of parameters for effective Web information retrieval using an evolutionary algorithm","authors":"J. Zakos, Ping Zhang, B. Verma","doi":"10.1109/IJCNN.2005.1555896","DOIUrl":"https://doi.org/10.1109/IJCNN.2005.1555896","url":null,"abstract":"In this paper we present an approach based on the application of an evolutionary algorithm to optimally tune the parameters of a novel technique for effective Web information retrieval. Context matching is a context-based technique for the ad-hoc retrieval of Web documents that relies on a number of inter-related parameters that define the nature of the context it uses. Its aim is to dynamically generate a context-based measure of term significance during retrieval that can be used as an indicator of document relevancy and ultimately contribute to a documents rank score. But the optimal setting of context matching parameters is an important aspect of the technique to ensure effective retrieval. Thus, the goal of this paper is to investigate the use of an evolutionary algorithm for the optimization of context matching parameters and compare its performance to an iterative technique that exhaustively explores combinations of parameters. We show how the most effective settings for parameters are obtained efficiently through the evolutionary algorithm. We also show how context matching, through the use of these optimized parameters, achieves effective retrieval results on benchmark data that are a significant improvement on previously published results.","PeriodicalId":365690,"journal":{"name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","volume":"146 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116411694","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
Determination of the optimal batch size in incremental approaches: an application to tornado detection 增量方法中最优批大小的确定:龙卷风探测中的应用
Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005. Pub Date : 2005-12-27 DOI: 10.1109/IJCNN.2005.1556352
H. Son, T. Trafalis, M. B. Richman
{"title":"Determination of the optimal batch size in incremental approaches: an application to tornado detection","authors":"H. Son, T. Trafalis, M. B. Richman","doi":"10.1109/IJCNN.2005.1556352","DOIUrl":"https://doi.org/10.1109/IJCNN.2005.1556352","url":null,"abstract":"Computing time and memory space limitations in applying support vector machines (SVMs) for large scale problems are recognized as critical limiting factors. Incremental approaches have serve as a remedy for large scale problems. However, determination of the appropriate batch size for incremental approaches has been explored rarely. In this study, the optimal batch size is defined as tradeoff between computing time and generalization error rate. Experiments for the determination of the optimal batch size, based on the mixture ratio of tornado and non-tornado data and a comparison between fixed batch size and knowledge based batch size, are performed. Preliminary results suggest that the knowledge based batch learning has the lowest generalization error rate.","PeriodicalId":365690,"journal":{"name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121927598","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: 6
Forecasting energy product prices 预测能源产品价格
Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005. Pub Date : 2005-12-27 DOI: 10.1109/IJCNN.2005.1556454
M. Malliaris, S. Malliaris
{"title":"Forecasting energy product prices","authors":"M. Malliaris, S. Malliaris","doi":"10.1109/IJCNN.2005.1556454","DOIUrl":"https://doi.org/10.1109/IJCNN.2005.1556454","url":null,"abstract":"Five inter-related energy products are forecasted one month into the future using both linear and nonlinear techniques. Both spot prices and data derived from those prices are used as input data in the models. The models are validated by running data from the following year. Results show that, even though all products are highly correlated, the prediction results are asymmetric. In forecasts for crude oil, heating oil, gasoline and natural gas, the nonlinear forecasts were best while for propane, the nonlinear model had the largest average absolute error.","PeriodicalId":365690,"journal":{"name":"Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121939906","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: 16
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