Pub Date : 1998-10-12DOI: 10.1109/ICOSP.1998.770260
S. Nishimura, Hai-Yun Jiang, T. Hinamoto
We present a new structure for complex adaptive IIR notch filters which is useful for the rejection of narrowband interference from broadband signals in QPSK communications systems. The proposed structure is based on a gradient algorithm. A performance analysis for convergence properties is developed. It is shown that the convergence speed does not depend on the variance of input white noise. The effects of colored Gaussian noise on convergence speed are analyzed. The results of computer simulation are shown which confirm the theoretical prediction.
{"title":"Performance analysis of complex adaptive IIR notch filters","authors":"S. Nishimura, Hai-Yun Jiang, T. Hinamoto","doi":"10.1109/ICOSP.1998.770260","DOIUrl":"https://doi.org/10.1109/ICOSP.1998.770260","url":null,"abstract":"We present a new structure for complex adaptive IIR notch filters which is useful for the rejection of narrowband interference from broadband signals in QPSK communications systems. The proposed structure is based on a gradient algorithm. A performance analysis for convergence properties is developed. It is shown that the convergence speed does not depend on the variance of input white noise. The effects of colored Gaussian noise on convergence speed are analyzed. The results of computer simulation are shown which confirm the theoretical prediction.","PeriodicalId":145700,"journal":{"name":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","volume":"180 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124500245","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}
Pub Date : 1998-10-12DOI: 10.1109/ICOSP.1998.770776
A. Košir, J. Tasic
Pattern spectrum is a shape size descriptor of the object content of a digital image. It is a technique for extracting shape and resolution information of a digital image. A discussion of the basic ideas of pattern spectrum is presented in the paper. Some useful features of the pattern spectrum concerning invariants for object recognition are derived. Features important for the calculation of the pattern spectrum are also included. The technique is applied to some typical shapes.
{"title":"Pattern spectrum of binary image","authors":"A. Košir, J. Tasic","doi":"10.1109/ICOSP.1998.770776","DOIUrl":"https://doi.org/10.1109/ICOSP.1998.770776","url":null,"abstract":"Pattern spectrum is a shape size descriptor of the object content of a digital image. It is a technique for extracting shape and resolution information of a digital image. A discussion of the basic ideas of pattern spectrum is presented in the paper. Some useful features of the pattern spectrum concerning invariants for object recognition are derived. Features important for the calculation of the pattern spectrum are also included. The technique is applied to some typical shapes.","PeriodicalId":145700,"journal":{"name":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124709023","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}
Pub Date : 1998-10-12DOI: 10.1109/ICOSP.1998.770830
S. Kai, Dong Shouping
Fuzzy logic analysis has been proven to be a simple and robust method for process control. In this paper the principle of fuzzy logic is applied to analyse the motion of the particles in a PIV (particle image velocimetry) image. The analysis is based on pattern recognition, and the patterns are composed of several adjacent particles. The principle of the decision making is based on the basic principles of fluid mechanics. As the particles move, the patterns change their shape and position in the second exposure, tracing the consequent matches of the corresponding patterns between two exposures the flow in a whole field will be obtained. A particle image-tracking algorithm based on this method is proposed and developed for the PIV image analysis. The pattern analysis executes in software on a PC without the use of specialised fuzzy logic processors. The objects of analysis were in both numerical simulated PIV images and an experimental PIV image. The results were encouraging.
{"title":"Fuzzy pattern recognition for PIV image analysis","authors":"S. Kai, Dong Shouping","doi":"10.1109/ICOSP.1998.770830","DOIUrl":"https://doi.org/10.1109/ICOSP.1998.770830","url":null,"abstract":"Fuzzy logic analysis has been proven to be a simple and robust method for process control. In this paper the principle of fuzzy logic is applied to analyse the motion of the particles in a PIV (particle image velocimetry) image. The analysis is based on pattern recognition, and the patterns are composed of several adjacent particles. The principle of the decision making is based on the basic principles of fluid mechanics. As the particles move, the patterns change their shape and position in the second exposure, tracing the consequent matches of the corresponding patterns between two exposures the flow in a whole field will be obtained. A particle image-tracking algorithm based on this method is proposed and developed for the PIV image analysis. The pattern analysis executes in software on a PC without the use of specialised fuzzy logic processors. The objects of analysis were in both numerical simulated PIV images and an experimental PIV image. The results were encouraging.","PeriodicalId":145700,"journal":{"name":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131739777","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}
Pub Date : 1998-10-12DOI: 10.1109/ICOSP.1998.770832
Yao Min, Zhang Sen
Fuzzy entropy is the measure of fuzziness in a fuzzy set. This paper proposes a kind of generalized fuzzy entropy which may describe various kinds of fuzzy entropy, and discusses its guidance functions in the design of fuzzy neural network classifiers.
{"title":"Generalized fuzzy entropy and its applications","authors":"Yao Min, Zhang Sen","doi":"10.1109/ICOSP.1998.770832","DOIUrl":"https://doi.org/10.1109/ICOSP.1998.770832","url":null,"abstract":"Fuzzy entropy is the measure of fuzziness in a fuzzy set. This paper proposes a kind of generalized fuzzy entropy which may describe various kinds of fuzzy entropy, and discusses its guidance functions in the design of fuzzy neural network classifiers.","PeriodicalId":145700,"journal":{"name":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134126045","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}
Pub Date : 1998-10-12DOI: 10.1109/ICOSP.1998.770934
M. Fukushima, H. Yanagawa, K. Kido
This paper proposes a method to improve the accuracy of the attenuation constant estimate obtained using the cross-spectral technique. In the cross-spectral technique, the envelope of the estimated impulse response is deformed due to the use of a time window. As a result, the estimated impulse response decays more rapidly than the real impulse response does and the attenuation constant obtained by the estimated impulse response becomes larger than the real value. This paper explains first how the attenuation constant changes in the process of impulse response estimation, next, the proposed method for improving the estimation accuracy.
{"title":"Improvement of the accuracy of attenuation constant estimation using the cross spectral technique","authors":"M. Fukushima, H. Yanagawa, K. Kido","doi":"10.1109/ICOSP.1998.770934","DOIUrl":"https://doi.org/10.1109/ICOSP.1998.770934","url":null,"abstract":"This paper proposes a method to improve the accuracy of the attenuation constant estimate obtained using the cross-spectral technique. In the cross-spectral technique, the envelope of the estimated impulse response is deformed due to the use of a time window. As a result, the estimated impulse response decays more rapidly than the real impulse response does and the attenuation constant obtained by the estimated impulse response becomes larger than the real value. This paper explains first how the attenuation constant changes in the process of impulse response estimation, next, the proposed method for improving the estimation accuracy.","PeriodicalId":145700,"journal":{"name":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134637794","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}
Pub Date : 1998-10-12DOI: 10.1109/ICOSP.1998.770956
I. Sadasiva, F. Flinders, W. Oghanna
A real time code generator which can generate 'C' code from a Simulink block diagram suitable for power electronic control applications has been developed. The 'C' code developed is down loaded to a digital signal processor control board. The software has been developed using Delphi. Three different types of control applications have been implemented on a PWM rectifier using the real time code generator. The paper compares the three different control systems implemented.
{"title":"An automatic block diagram to 'C' code generator for power electronic control applications","authors":"I. Sadasiva, F. Flinders, W. Oghanna","doi":"10.1109/ICOSP.1998.770956","DOIUrl":"https://doi.org/10.1109/ICOSP.1998.770956","url":null,"abstract":"A real time code generator which can generate 'C' code from a Simulink block diagram suitable for power electronic control applications has been developed. The 'C' code developed is down loaded to a digital signal processor control board. The software has been developed using Delphi. Three different types of control applications have been implemented on a PWM rectifier using the real time code generator. The paper compares the three different control systems implemented.","PeriodicalId":145700,"journal":{"name":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131868791","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}
Pub Date : 1998-10-12DOI: 10.1109/ICOSP.1998.770876
Fan Longfei, Zheng Hui, Zhao Guangming, H. Shun-ji
Complex signal and system models are considered in this paper, and a class of new criteria, which is based on the higher-order cumulant, is derived for blind deconvolution. It is pointed out that blind deconvolution may be realized by maximizing or minimizing the normalized cumulant of the system output. This is a new approach to statistical matching for blind deconvolution. As an example, a new blind deconvolution (equalization) algorithm is proposed, and computer simulation results are included to demonstrate the performance of the proposed algorithm.
{"title":"A class of new criteria for blind deconvolution","authors":"Fan Longfei, Zheng Hui, Zhao Guangming, H. Shun-ji","doi":"10.1109/ICOSP.1998.770876","DOIUrl":"https://doi.org/10.1109/ICOSP.1998.770876","url":null,"abstract":"Complex signal and system models are considered in this paper, and a class of new criteria, which is based on the higher-order cumulant, is derived for blind deconvolution. It is pointed out that blind deconvolution may be realized by maximizing or minimizing the normalized cumulant of the system output. This is a new approach to statistical matching for blind deconvolution. As an example, a new blind deconvolution (equalization) algorithm is proposed, and computer simulation results are included to demonstrate the performance of the proposed algorithm.","PeriodicalId":145700,"journal":{"name":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","volume":"126 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131694610","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}
Pub Date : 1998-10-12DOI: 10.1109/ICOSP.1998.770913
L. Yonghong, Qiu Fuxiang, Yang Guangzhi
This paper presents a novel method to solve the problem of smoothing and prediction in real-time in marine radar tracking by means of a feedforward neural network, which is able to deal with any kind of target data. Varying steps are employed in the network training in addition to the momentum factor. Simulation results show that the predictive track error is rapidly convergent and the accuracy of stable tracking is good enough for marine radar data processing, especially for a ship with a speed below 2O nm/h. The network can also track the target in time which takes a sudden turn.
{"title":"Research on the feedforward network method of marine radar track","authors":"L. Yonghong, Qiu Fuxiang, Yang Guangzhi","doi":"10.1109/ICOSP.1998.770913","DOIUrl":"https://doi.org/10.1109/ICOSP.1998.770913","url":null,"abstract":"This paper presents a novel method to solve the problem of smoothing and prediction in real-time in marine radar tracking by means of a feedforward neural network, which is able to deal with any kind of target data. Varying steps are employed in the network training in addition to the momentum factor. Simulation results show that the predictive track error is rapidly convergent and the accuracy of stable tracking is good enough for marine radar data processing, especially for a ship with a speed below 2O nm/h. The network can also track the target in time which takes a sudden turn.","PeriodicalId":145700,"journal":{"name":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","volume":"419 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133760922","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}
Pub Date : 1998-10-12DOI: 10.1109/ICOSP.1998.770839
Dequan Zhou, Liguang Wu, G. Liu
Bayesian decision theory is widely used in pattern recognition and signal detection. Only when the class-conditional-probability density is known can the theory be used. A discretization method of stochastic variable (feature) space of the class-conditional-probability-density, and an estimation method for the class-conditional-probability-distribution are proposed. A Bayesian classification algorithm based on the methods is given. Finally, the methods are illustrated by applying them to radar target recognition.
{"title":"Bayesian classifier based on discretized continuous feature space","authors":"Dequan Zhou, Liguang Wu, G. Liu","doi":"10.1109/ICOSP.1998.770839","DOIUrl":"https://doi.org/10.1109/ICOSP.1998.770839","url":null,"abstract":"Bayesian decision theory is widely used in pattern recognition and signal detection. Only when the class-conditional-probability density is known can the theory be used. A discretization method of stochastic variable (feature) space of the class-conditional-probability-density, and an estimation method for the class-conditional-probability-distribution are proposed. A Bayesian classification algorithm based on the methods is given. Finally, the methods are illustrated by applying them to radar target recognition.","PeriodicalId":145700,"journal":{"name":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133244579","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}
Pub Date : 1998-10-12DOI: 10.1109/ICOSP.1998.770786
H.R. Wu, T. Ferguson, B. Qiu
This paper addresses the importance of quality assessment and control of digital video using psychovisual-based quantitative quality metrics. Three newly-introduced such metrics are evaluated using various video sequences coded at different rates by ITU-T H.263 and MPEG-2-compliant codecs.
{"title":"Digital video quality evaluation using quantitative quality metrics","authors":"H.R. Wu, T. Ferguson, B. Qiu","doi":"10.1109/ICOSP.1998.770786","DOIUrl":"https://doi.org/10.1109/ICOSP.1998.770786","url":null,"abstract":"This paper addresses the importance of quality assessment and control of digital video using psychovisual-based quantitative quality metrics. Three newly-introduced such metrics are evaluated using various video sequences coded at different rates by ITU-T H.263 and MPEG-2-compliant codecs.","PeriodicalId":145700,"journal":{"name":"ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132590453","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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