Pub Date : 2008-12-08DOI: 10.1109/ICOSP.2008.4697516
Zhibin Xie, Jinkuan Wang, Jing Gao, Yun Wang, Dongmei Yan
The multi-antenna system can significantly increase the spectral efficiency of wireless systems. This paper proposes a novel low complexity preprocessing scheme for multiuser multiple-input multiple-output (MU-MIMO) system. The proposed precoding algorithm decomposes the composite downlink channel into the multiple sub-channels without inter-user interference and has lower cost than traditional algorithms. At the same time, an efficient equalization algorithm is proposed to achieve the joint optimal design in receiver. Simulation results show the feasibility and effectiveness of the proposed algorithm.
{"title":"Efficient transmit and receive optimization design for multiuser spatial multiplexing systems","authors":"Zhibin Xie, Jinkuan Wang, Jing Gao, Yun Wang, Dongmei Yan","doi":"10.1109/ICOSP.2008.4697516","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697516","url":null,"abstract":"The multi-antenna system can significantly increase the spectral efficiency of wireless systems. This paper proposes a novel low complexity preprocessing scheme for multiuser multiple-input multiple-output (MU-MIMO) system. The proposed precoding algorithm decomposes the composite downlink channel into the multiple sub-channels without inter-user interference and has lower cost than traditional algorithms. At the same time, an efficient equalization algorithm is proposed to achieve the joint optimal design in receiver. Simulation results show the feasibility and effectiveness of the proposed algorithm.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127799188","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 : 2008-12-08DOI: 10.1109/ICOSP.2008.4697623
Changzheng Ma, T. Yeo, Junjie Feng, H. Tan
Multiple input multiple output (MIMO) radar transmits orthogonal or non-coherent waveforms which greatly improve the array aperture. Works published generally only consider narrow band signal and/or point targets located in one range cell. In this paper, the study of range and azimuth angle imaging of extended targets employing wideband hopped frequency signals is discussed. Hopped frequency signal are sensitive to a targetpsilas speed. A kurtosis based criterion is presented for doing motion compensation. In order to mitigate the high side lobe of the hopped frequency signal, a ldquoCLEANrdquo based signal processing procedure is also presented.
{"title":"Two dimensional imaging of extended targets by MIMO radar using hopped frequency signal","authors":"Changzheng Ma, T. Yeo, Junjie Feng, H. Tan","doi":"10.1109/ICOSP.2008.4697623","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697623","url":null,"abstract":"Multiple input multiple output (MIMO) radar transmits orthogonal or non-coherent waveforms which greatly improve the array aperture. Works published generally only consider narrow band signal and/or point targets located in one range cell. In this paper, the study of range and azimuth angle imaging of extended targets employing wideband hopped frequency signals is discussed. Hopped frequency signal are sensitive to a targetpsilas speed. A kurtosis based criterion is presented for doing motion compensation. In order to mitigate the high side lobe of the hopped frequency signal, a ldquoCLEANrdquo based signal processing procedure is also presented.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134473507","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 : 2008-12-08DOI: 10.1109/ICOSP.2008.4697556
Changling Wang, Shangling Song, Fengrong Sun, Liangmo Mei
Humanpsilas finger-articular back texture(FABT), as a novel biometric identification pattern, has been studied. As a basis set of FABT space, eigenjoints are extracted by principle component analysis. The features of each finger-articular back texture are computed by projecting on the related eigenjoint space. In matching stage, the decision are made by using nearest neighbor classifier based on Mahalanobis distance. The results show that: back finger- joint texture has high uniqueness in terms of high recognition accuracy rate (97.57 percent); the inter-class and intra-class have good separability; and recognition speed is fast enough for real time identification.
{"title":"Study on Finger-Articular Back Texture recognition","authors":"Changling Wang, Shangling Song, Fengrong Sun, Liangmo Mei","doi":"10.1109/ICOSP.2008.4697556","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697556","url":null,"abstract":"Humanpsilas finger-articular back texture(FABT), as a novel biometric identification pattern, has been studied. As a basis set of FABT space, eigenjoints are extracted by principle component analysis. The features of each finger-articular back texture are computed by projecting on the related eigenjoint space. In matching stage, the decision are made by using nearest neighbor classifier based on Mahalanobis distance. The results show that: back finger- joint texture has high uniqueness in terms of high recognition accuracy rate (97.57 percent); the inter-class and intra-class have good separability; and recognition speed is fast enough for real time identification.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131872241","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 : 2008-12-08DOI: 10.1109/ICOSP.2008.4697456
Hongyan Wang, Jinwen Ma
In this paper, a Bayesian Ying-Yang (BYY) harmony enforcing regularization (BYY-HER) algorithm is proposed for Gaussian mixture learning with a sample dataset on both parameter estimation and model selection, i.e., selecting an appropriate number of Gaussians in the mixture, through a regularization process from the BYY harmony learning to the maximum likelihood learning. It has been demonstrated by experiments on synthetical and real sample datasets that our proposed BYY-HER algorithm can not only select the correct number of actual Gaussians in a dataset, but also obtain good parameter estimations for the parameters in the true mixture.
{"title":"BYY harmony enforcing regularization for gaussian mixture learning","authors":"Hongyan Wang, Jinwen Ma","doi":"10.1109/ICOSP.2008.4697456","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697456","url":null,"abstract":"In this paper, a Bayesian Ying-Yang (BYY) harmony enforcing regularization (BYY-HER) algorithm is proposed for Gaussian mixture learning with a sample dataset on both parameter estimation and model selection, i.e., selecting an appropriate number of Gaussians in the mixture, through a regularization process from the BYY harmony learning to the maximum likelihood learning. It has been demonstrated by experiments on synthetical and real sample datasets that our proposed BYY-HER algorithm can not only select the correct number of actual Gaussians in a dataset, but also obtain good parameter estimations for the parameters in the true mixture.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115586171","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 : 2008-12-08DOI: 10.1109/ICOSP.2008.4697659
Fan Chong-yi, Huang Xiaotao, Chang Wen-ge
Fractional Fourier Transform (FRFT) has been widely used in chirp signal processing. This paper is based on the former research work and realized a FRFT application on the imaging processing with real raw data of Synthetic Aperture Radar (SAR.) It connected the fast discrete computation of FRFT and explained the principle of pulse compression in FRFT processing. Comparing with the classical pulse compression, FRFT has the similar processing expect a different modulation window, which brings equivalent performance in Signal to Noise Ratio (SNR) and lower sidelobe. Then a linear low pass filter was designed to utilize this character and restrain the great shading effect. This easy but effective method managed to replace the range pulse compression processing by FRFT, which was proved by the result with real raw data.
{"title":"Replacing the pulse compressing by FRFT on imaging processing with real raw data of SAR","authors":"Fan Chong-yi, Huang Xiaotao, Chang Wen-ge","doi":"10.1109/ICOSP.2008.4697659","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697659","url":null,"abstract":"Fractional Fourier Transform (FRFT) has been widely used in chirp signal processing. This paper is based on the former research work and realized a FRFT application on the imaging processing with real raw data of Synthetic Aperture Radar (SAR.) It connected the fast discrete computation of FRFT and explained the principle of pulse compression in FRFT processing. Comparing with the classical pulse compression, FRFT has the similar processing expect a different modulation window, which brings equivalent performance in Signal to Noise Ratio (SNR) and lower sidelobe. Then a linear low pass filter was designed to utilize this character and restrain the great shading effect. This easy but effective method managed to replace the range pulse compression processing by FRFT, which was proved by the result with real raw data.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115623291","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 : 2008-12-08DOI: 10.1109/ICOSP.2008.4697683
J. Nishimura, T. Kuroda
Haar-like filtering based speech detection is proposed as a new and very low calculation cost method for sensornet applications. The simple Haar-like filters having variable filter width and shift width are trained to learn appropriate filter parameters from the training samples to detect speech. Our method yielded speech/nonspeech classification accuracy of 96.93% for the input length of 0.1s. Compared with high performance feature extraction method MFCC (Mel-frequency cepstrum coefficient), the proposed Haar-like filtering can be approximately 85.77% efficient in terms of the amount of add and multiply calculations while capable of achieving the error rate of only 3.03% relative to MFCC.
{"title":"Low cost speech detection using Haar-like filtering for sensornet","authors":"J. Nishimura, T. Kuroda","doi":"10.1109/ICOSP.2008.4697683","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697683","url":null,"abstract":"Haar-like filtering based speech detection is proposed as a new and very low calculation cost method for sensornet applications. The simple Haar-like filters having variable filter width and shift width are trained to learn appropriate filter parameters from the training samples to detect speech. Our method yielded speech/nonspeech classification accuracy of 96.93% for the input length of 0.1s. Compared with high performance feature extraction method MFCC (Mel-frequency cepstrum coefficient), the proposed Haar-like filtering can be approximately 85.77% efficient in terms of the amount of add and multiply calculations while capable of achieving the error rate of only 3.03% relative to MFCC.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115703650","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 : 2008-12-08DOI: 10.1109/ICOSP.2008.4697222
Haiyan Guo, Xi Shao, Zhen Yang
This paper presents an improved phase-space voicing state classification method based on pitch detection to simultaneously determine the voicing state of two speakers present in a segment of co-channel speech. Three possible voicing states are considered: Unvoiced/Unvoiced (U/U), Voice/Unvoiced (V/U), Voiced/Voiced (V/V). Firstly, the method employs a phase-space voicing-state classification algorithm to classify co-channel speech into three parts: U/U frames, V/U frames and V/V frames. Secondly, in order to decrease misjudgment between V/U and V/V frames, we introduce mulitpitch detection based on enhanced summary autocorrelation function (ESACF) to modify the voicing states of V/V frames and single pitch detection based on autocorrelation function (ACF) to modify the voicing states of V/U frames. Experiments show the proposed method effectively reduces the classification error rate and outperforms the voicing-state classification algorithm only based on phase-space reconstruction.
{"title":"An improved phase-space voicing-state classification for co-channel speech based on pitch detection","authors":"Haiyan Guo, Xi Shao, Zhen Yang","doi":"10.1109/ICOSP.2008.4697222","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697222","url":null,"abstract":"This paper presents an improved phase-space voicing state classification method based on pitch detection to simultaneously determine the voicing state of two speakers present in a segment of co-channel speech. Three possible voicing states are considered: Unvoiced/Unvoiced (U/U), Voice/Unvoiced (V/U), Voiced/Voiced (V/V). Firstly, the method employs a phase-space voicing-state classification algorithm to classify co-channel speech into three parts: U/U frames, V/U frames and V/V frames. Secondly, in order to decrease misjudgment between V/U and V/V frames, we introduce mulitpitch detection based on enhanced summary autocorrelation function (ESACF) to modify the voicing states of V/V frames and single pitch detection based on autocorrelation function (ACF) to modify the voicing states of V/U frames. Experiments show the proposed method effectively reduces the classification error rate and outperforms the voicing-state classification algorithm only based on phase-space reconstruction.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"1164 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124348609","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 : 2008-12-08DOI: 10.1109/ICOSP.2008.4697645
Sijie Yuan, Tao Wu, Mao Mao, G. Mei, Xin Wei
Because of the high speed and the long repeat interval of the radar, there would be serious echo envelope migration while using low-PRF narrowband chirp radar to detect weak high speed targets. The coherent integration method of envelope migration compensation based on keystone transform is studied, the problem of Doppler ambiguity is analyzed, and the influence on the coherent integration effect of Doppler ambiguity degree error and signal band width is simulated, which helps to determine the step of Doppler ambiguity degree search step. The algorithm is introduced and finally experiments on real data are made to testify the algorithm. The results of 128 echo pulses procession show that the SNR could be enhanced by 6 dB, which confirm the effectiveness of this method and improve the ability of weak high speed target detection.
{"title":"Application research of keystone transform in weak high-speed target detection in low-PRF narrowband Chirp radar","authors":"Sijie Yuan, Tao Wu, Mao Mao, G. Mei, Xin Wei","doi":"10.1109/ICOSP.2008.4697645","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697645","url":null,"abstract":"Because of the high speed and the long repeat interval of the radar, there would be serious echo envelope migration while using low-PRF narrowband chirp radar to detect weak high speed targets. The coherent integration method of envelope migration compensation based on keystone transform is studied, the problem of Doppler ambiguity is analyzed, and the influence on the coherent integration effect of Doppler ambiguity degree error and signal band width is simulated, which helps to determine the step of Doppler ambiguity degree search step. The algorithm is introduced and finally experiments on real data are made to testify the algorithm. The results of 128 echo pulses procession show that the SNR could be enhanced by 6 dB, which confirm the effectiveness of this method and improve the ability of weak high speed target detection.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"487 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124421071","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}
Noise frequency modulated (NFM) interference causes a disaster to almost all types of radar systems. The echo signal and the interference are overlapped because of the strong energy of the NFM interference, and in the radar receiver system nothing could be detected except the interference. Up to now no good method against NFM has been declared, conventional methods are based on the passive radar to track the interference source. Here a new anti-noise FM method is proposed to suppress the NFM interference, the method multiply the echo signal two times by different reference signals, and results show that the method can eradicate NFM effectively which is useful for detecting and tracking the target. Whatpsilas more, in the presence of several interferences from different directions, the passive Radar can not track the interference source but the method supposed here can work well.
{"title":"A new method for anti-noise FM interference","authors":"Changyong Jiang, M. Gao, Defeng Chen","doi":"10.4236/wsn.2009.14036","DOIUrl":"https://doi.org/10.4236/wsn.2009.14036","url":null,"abstract":"Noise frequency modulated (NFM) interference causes a disaster to almost all types of radar systems. The echo signal and the interference are overlapped because of the strong energy of the NFM interference, and in the radar receiver system nothing could be detected except the interference. Up to now no good method against NFM has been declared, conventional methods are based on the passive radar to track the interference source. Here a new anti-noise FM method is proposed to suppress the NFM interference, the method multiply the echo signal two times by different reference signals, and results show that the method can eradicate NFM effectively which is useful for detecting and tracking the target. Whatpsilas more, in the presence of several interferences from different directions, the passive Radar can not track the interference source but the method supposed here can work well.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124536724","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 : 2008-12-08DOI: 10.1109/ICOSP.2008.4697079
Xin Xu, Nan Zhao, Hang Dong
Particle filters have been proposed as a new form of state-space filtering for speech enhancement applications. A crucial issue in particle filtering is the selection of the importance proposal distribution. In this paper, the iterated extended Kalman filter (IEKF) is used to generate the proposal distribution. The proposal distribution integrates the latest measurements into state transition density, so it can match the posteriori density well. We apply time-varying autoregressive (TVAR) models with stochastically evolving parameters to the problem of speech modeling and enhancement, which is superior to conventional AR models. The experimental results indicate that the new particle filter superiors to the standard particle filter and the other filters such as the extended Kalman particle filter (PF-EKF) in low SNR.
{"title":"The iterated extended kalman particle filter for speech enhancement","authors":"Xin Xu, Nan Zhao, Hang Dong","doi":"10.1109/ICOSP.2008.4697079","DOIUrl":"https://doi.org/10.1109/ICOSP.2008.4697079","url":null,"abstract":"Particle filters have been proposed as a new form of state-space filtering for speech enhancement applications. A crucial issue in particle filtering is the selection of the importance proposal distribution. In this paper, the iterated extended Kalman filter (IEKF) is used to generate the proposal distribution. The proposal distribution integrates the latest measurements into state transition density, so it can match the posteriori density well. We apply time-varying autoregressive (TVAR) models with stochastically evolving parameters to the problem of speech modeling and enhancement, which is superior to conventional AR models. The experimental results indicate that the new particle filter superiors to the standard particle filter and the other filters such as the extended Kalman particle filter (PF-EKF) in low SNR.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114319086","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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