P. Salvatori, A. Neri, C. Stallo, Veronica Palma, A. Coluccia, F. Rispoli
The paper describes the performance comparison between EGNOS system and an Augmentation & Integrity Monitoring Network (AIMN) Location Determination System (LDS) designed for train positioning in terms of PVT accuracy and integrity information. The proposed work is inserted in the scenario of introduction and application of space technologies based on the ERTMS architecture. It foresees to include the EGNOS-Galileo infrastructures in the train control system, with the aim at improving performance, enhancing safety and reducing the investments on the railways circuitry and its maintenance. The performance results will be shown, based on a campaign test acquired on a ring-shaped highway (named Grande Raccordo Anulare (GRA)) around Rome (Italy) to simulate movement of a train on a generic track.
{"title":"Augmentation and Integrity Monitoring Network and EGNOS performance comparison for train positioning","authors":"P. Salvatori, A. Neri, C. Stallo, Veronica Palma, A. Coluccia, F. Rispoli","doi":"10.5281/ZENODO.44035","DOIUrl":"https://doi.org/10.5281/ZENODO.44035","url":null,"abstract":"The paper describes the performance comparison between EGNOS system and an Augmentation & Integrity Monitoring Network (AIMN) Location Determination System (LDS) designed for train positioning in terms of PVT accuracy and integrity information. The proposed work is inserted in the scenario of introduction and application of space technologies based on the ERTMS architecture. It foresees to include the EGNOS-Galileo infrastructures in the train control system, with the aim at improving performance, enhancing safety and reducing the investments on the railways circuitry and its maintenance. The performance results will be shown, based on a campaign test acquired on a ring-shaped highway (named Grande Raccordo Anulare (GRA)) around Rome (Italy) to simulate movement of a train on a generic track.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122237899","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}
Biometrics are quantities obtained from analyses of biological measurements. For human based biometrics, the two main types are clinical and authentication. This paper presents a brief comparison between the two, showing that on many occasions clinical biometrics can motivate for its use in authentication applications. Since several clinical biometrics deal with temporal data and also involve several dimensions of movement, we also present a new application of Singular Spectrum Analysis, in particular its multivariate version, to obtain significant frequency information across these dimensions. We use the most significant frequency component as a biometric to distinguish between various types of human movements. The signals were collected from triaxial accelerometers mounted in an object that is handled by a user. Although this biometric was obtained in a clinical setting, it shows promise for authentication.
{"title":"A multivariate Singular Spectrum Analysis approach to clinically-motivated movement biometrics","authors":"T. Lee, S. Gan, J. G. Lim, S. Sanei","doi":"10.5281/ZENODO.43824","DOIUrl":"https://doi.org/10.5281/ZENODO.43824","url":null,"abstract":"Biometrics are quantities obtained from analyses of biological measurements. For human based biometrics, the two main types are clinical and authentication. This paper presents a brief comparison between the two, showing that on many occasions clinical biometrics can motivate for its use in authentication applications. Since several clinical biometrics deal with temporal data and also involve several dimensions of movement, we also present a new application of Singular Spectrum Analysis, in particular its multivariate version, to obtain significant frequency information across these dimensions. We use the most significant frequency component as a biometric to distinguish between various types of human movements. The signals were collected from triaxial accelerometers mounted in an object that is handled by a user. Although this biometric was obtained in a clinical setting, it shows promise for authentication.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121035122","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}
We discuss a few promising applications of the faster-than-Nyquist (FTN) signaling technique. Although proposed in the mid 70s, thanks to recent extensions this technique is taking on a new lease of life. In particular, we will discuss its applications to satellite systems for broadcasting transmissions, optical long-haul transmissions, and next-generation cellular systems, possibly equipped with a large scale antenna system (LSAS) at the base stations (BSs). Moreover, based on measurements with a 128 element antenna array, we analyze the spectral efficiency that can be achieved with simple receiver solutions in single carrier LSAS systems.
{"title":"Faster-than-Nyquist signaling for next generation communication architectures","authors":"Andrea Modenini, F. Rusek, G. Colavolpe","doi":"10.5281/ZENODO.44213","DOIUrl":"https://doi.org/10.5281/ZENODO.44213","url":null,"abstract":"We discuss a few promising applications of the faster-than-Nyquist (FTN) signaling technique. Although proposed in the mid 70s, thanks to recent extensions this technique is taking on a new lease of life. In particular, we will discuss its applications to satellite systems for broadcasting transmissions, optical long-haul transmissions, and next-generation cellular systems, possibly equipped with a large scale antenna system (LSAS) at the base stations (BSs). Moreover, based on measurements with a 128 element antenna array, we analyze the spectral efficiency that can be achieved with simple receiver solutions in single carrier LSAS systems.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125154280","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}
We study the problem of sequential prediction of real-valued sequences under the squared error loss function. While refraining from any statistical and structural assumptions on the underlying sequence, we introduce a competitive approach to this problem and compare the performance of a sequential algorithm with respect to the large and continuous class of parametric predictors. We define the performance difference between a sequential algorithm and the best parametric predictor as “regret”, and introduce a guaranteed worst-case lower bounds to this relative performance measure. In particular, we prove that for any sequential algorithm, there always exists a sequence for which this regret is lower bounded by zero. We then extend this result by showing that the prediction problem can be transformed into a parameter estimation problem if the class of parametric predictors satisfy a certain property, and provide a comprehensive lower bound to this case.
{"title":"Comprehensive lower bounds on sequential prediction","authors":"N. D. Vanli, M. O. Sayin, S. Ergüt, S. Kozat","doi":"10.5281/ZENODO.44015","DOIUrl":"https://doi.org/10.5281/ZENODO.44015","url":null,"abstract":"We study the problem of sequential prediction of real-valued sequences under the squared error loss function. While refraining from any statistical and structural assumptions on the underlying sequence, we introduce a competitive approach to this problem and compare the performance of a sequential algorithm with respect to the large and continuous class of parametric predictors. We define the performance difference between a sequential algorithm and the best parametric predictor as “regret”, and introduce a guaranteed worst-case lower bounds to this relative performance measure. In particular, we prove that for any sequential algorithm, there always exists a sequence for which this regret is lower bounded by zero. We then extend this result by showing that the prediction problem can be transformed into a parameter estimation problem if the class of parametric predictors satisfy a certain property, and provide a comprehensive lower bound to this case.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131179765","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}
High mobility of terminals constitutes a hot topic that is commonly envisaged for the next Fifth Generation (5G) of mobile communication systems. The wireless propagation channel is a time-frequency variant. This aspect can dramatically damage the waveforms orthogonality that is induced in the Orthogonal frequency division multiplexing (OFDM) signal. Consequently, this results in oppressive Inter-Carrier Interference (ICI) and Inter-Symbol Interference (ISI), which leads to performance degradation in OFDM systems. To efficiently overcome these drawbacks, we developed in [1] an adequate algorithm that maximizes the received Signal to Interference plus Noise Ratio (SINR) by optimizing systematically the OFDM waveforms at the Transmitter (TX) and Receiver (RX) sides. In this paper, we go further by investigating the performance evaluation of this algorithm. We start by testing its robustness against time and frequency synchronization errors. Then, as this algorithm banks on an iterative approach to find the optimal waveforms, we study the impact of the waveform initialization on its convergence. The obtained simulation results confirm the efficiency of this algorithm and its robustness compared to the conventional OFDM schemes, which makes it an appropriate good candidate for 5G systems.
{"title":"Numerical characterization for optimal designed waveform to multicarrier systems in 5G","authors":"Zeineb Hraiech, M. Siala, F. Abdelkefi","doi":"10.5281/ZENODO.43999","DOIUrl":"https://doi.org/10.5281/ZENODO.43999","url":null,"abstract":"High mobility of terminals constitutes a hot topic that is commonly envisaged for the next Fifth Generation (5G) of mobile communication systems. The wireless propagation channel is a time-frequency variant. This aspect can dramatically damage the waveforms orthogonality that is induced in the Orthogonal frequency division multiplexing (OFDM) signal. Consequently, this results in oppressive Inter-Carrier Interference (ICI) and Inter-Symbol Interference (ISI), which leads to performance degradation in OFDM systems. To efficiently overcome these drawbacks, we developed in [1] an adequate algorithm that maximizes the received Signal to Interference plus Noise Ratio (SINR) by optimizing systematically the OFDM waveforms at the Transmitter (TX) and Receiver (RX) sides. In this paper, we go further by investigating the performance evaluation of this algorithm. We start by testing its robustness against time and frequency synchronization errors. Then, as this algorithm banks on an iterative approach to find the optimal waveforms, we study the impact of the waveform initialization on its convergence. The obtained simulation results confirm the efficiency of this algorithm and its robustness compared to the conventional OFDM schemes, which makes it an appropriate good candidate for 5G systems.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121643668","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}
Dumidu S. Talagala, Xiang Wu, Wen Zhang, T. Abhayapala
In binaural systems, source localization in the median plane is challenging due to the difficulty of exploring the spectral cues of the head-related transfer function (HRTF) independently of the source spectra. This paper presents a method of extracting the HRTF spectral cues using cepstral analysis for speech source localization in the median plane. Binaural signals are preprocessed in the cepstral domain so that the fine spectral structure of speech and the HRTF spectral envelope can be easily separated. We introduce (i) a truncated cepstral transformation to extract the relevant localization cues, and (ii) a mechanism to normalize the effects of the time varying speech spectra. The proposed method is evaluated and compared with a convolution based localization method using a speech corpus of multiple speakers. The results suggest that the proposed method fully exploits the available spectral cues for robust speaker independent binaural source localization in the median plane.
{"title":"Binaural localization of speech sources in the median plane using cepstral hrtf extraction","authors":"Dumidu S. Talagala, Xiang Wu, Wen Zhang, T. Abhayapala","doi":"10.5281/ZENODO.44021","DOIUrl":"https://doi.org/10.5281/ZENODO.44021","url":null,"abstract":"In binaural systems, source localization in the median plane is challenging due to the difficulty of exploring the spectral cues of the head-related transfer function (HRTF) independently of the source spectra. This paper presents a method of extracting the HRTF spectral cues using cepstral analysis for speech source localization in the median plane. Binaural signals are preprocessed in the cepstral domain so that the fine spectral structure of speech and the HRTF spectral envelope can be easily separated. We introduce (i) a truncated cepstral transformation to extract the relevant localization cues, and (ii) a mechanism to normalize the effects of the time varying speech spectra. The proposed method is evaluated and compared with a convolution based localization method using a speech corpus of multiple speakers. The results suggest that the proposed method fully exploits the available spectral cues for robust speaker independent binaural source localization in the median plane.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131946007","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}
Super Gaussian (SG) distributions have proven to be very powerful prior models to induce sparsity in Bayesian Blind Deconvolution (BD) problems. Their conjugate based representations make them specially attractive when Variational Bayes (VB) inference is used since their variational parameters can be calculated in closed form with the sole knowledge of the energy function of the prior model. In this work we show how the introduction in the SG distribution of a global strength (not necessary scale) parameter can be used to improve the quality of the obtained restorations as well as to introduce additional information on the global weight of the prior. A model to estimate the new unknown parameter within the Bayesian framework is provided. Experimental results, on both synthetic and real images, demonstrate the effectiveness of the proposed approach.
{"title":"Parameter estimation in Bayesian Blind Deconvolution with super Gaussian image priors","authors":"M. Vega, R. Molina, A. Katsaggelos","doi":"10.5281/ZENODO.43886","DOIUrl":"https://doi.org/10.5281/ZENODO.43886","url":null,"abstract":"Super Gaussian (SG) distributions have proven to be very powerful prior models to induce sparsity in Bayesian Blind Deconvolution (BD) problems. Their conjugate based representations make them specially attractive when Variational Bayes (VB) inference is used since their variational parameters can be calculated in closed form with the sole knowledge of the energy function of the prior model. In this work we show how the introduction in the SG distribution of a global strength (not necessary scale) parameter can be used to improve the quality of the obtained restorations as well as to introduce additional information on the global weight of the prior. A model to estimate the new unknown parameter within the Bayesian framework is provided. Experimental results, on both synthetic and real images, demonstrate the effectiveness of the proposed approach.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134470351","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}
A. Lavrenko, F. Roemer, G. D. Galdo, R. Thomä, O. Arikan
Compressed sensing allows for a significant reduction of the number of measurements when the signal of interest is of a sparse nature. Most computationally efficient algorithms for signal recovery rely on some knowledge of the sparsity level, i.e., the number of non-zero elements. However, the sparsity level is often not known a priori and can even vary with time. In this contribution we show that it is possible to estimate the sparsity level directly in the compressed domain, provided that multiple independent observations are available. In fact, one can use classical model order selection algorithms for this purpose. Nevertheless, due to the influence of the measurement process they may not perform satisfactorily in the compressed sensing setup. To overcome this drawback, we propose an approach which exploits the empirical distributions of the noise eigenvalues. We demonstrate its superior performance compared to state-of-the-art model order estimation algorithms numerically.
{"title":"An empirical eigenvalue-threshold test for sparsity level estimation from compressed measurements","authors":"A. Lavrenko, F. Roemer, G. D. Galdo, R. Thomä, O. Arikan","doi":"10.5281/ZENODO.44108","DOIUrl":"https://doi.org/10.5281/ZENODO.44108","url":null,"abstract":"Compressed sensing allows for a significant reduction of the number of measurements when the signal of interest is of a sparse nature. Most computationally efficient algorithms for signal recovery rely on some knowledge of the sparsity level, i.e., the number of non-zero elements. However, the sparsity level is often not known a priori and can even vary with time. In this contribution we show that it is possible to estimate the sparsity level directly in the compressed domain, provided that multiple independent observations are available. In fact, one can use classical model order selection algorithms for this purpose. Nevertheless, due to the influence of the measurement process they may not perform satisfactorily in the compressed sensing setup. To overcome this drawback, we propose an approach which exploits the empirical distributions of the noise eigenvalues. We demonstrate its superior performance compared to state-of-the-art model order estimation algorithms numerically.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129111742","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}
Reduction of the out-of-band (OOB) emission is essential for Cognitive Radio (CR) systems to enable coexistence with licensed (primary) systems operating in the adjacent frequency bands. This paper proposes an algorithm for the Non Contiguous Orthogonal Frequency Division Multiplexing (NC-OFDM)-based CR, to reduce the interference caused by both OOB radiation and by non-ideal frequency selectivity of a primary user (PU) receiver. It is based on a concept to use a set of subcarriers called Cancellation Carriers (CCs). By being aware of the PU's carrier frequency, the observed interference power can by decreased by about 10 dB in comparison with the standard OOB-power minimizing algorithms.
{"title":"Advanced interference reduction in NC-OFDM based Cognitive Radio with Cancellation Carriers","authors":"P. Kryszkiewicz, H. Bogucka","doi":"10.5281/ZENODO.43848","DOIUrl":"https://doi.org/10.5281/ZENODO.43848","url":null,"abstract":"Reduction of the out-of-band (OOB) emission is essential for Cognitive Radio (CR) systems to enable coexistence with licensed (primary) systems operating in the adjacent frequency bands. This paper proposes an algorithm for the Non Contiguous Orthogonal Frequency Division Multiplexing (NC-OFDM)-based CR, to reduce the interference caused by both OOB radiation and by non-ideal frequency selectivity of a primary user (PU) receiver. It is based on a concept to use a set of subcarriers called Cancellation Carriers (CCs). By being aware of the PU's carrier frequency, the observed interference power can by decreased by about 10 dB in comparison with the standard OOB-power minimizing algorithms.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132218872","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}
We propose a method for vocal tract estimation that is better than Bozkurt's chirp group delay method [1] and its zero-phase variant [2]. The chirp group delay method works only for voiced speech, is critically dependent on finding the glottal closure instants (GCI), deteriorates in performance when more than two pitch cycles are included for analysis, and does not work for unvoiced speech. The zero-phase variant eliminates these drawbacks but works poorly for nasal sounds. In our proposed method all outside-unit-circle zeros are reflected inside before computing the chirp group delay. The advantages are: (a) GCI knowledge not required, (b) the vocal tract estimate is far less sensitive to the location and duration of the analysis window, (c) works for unvoiced sounds, and (d) captures the spectral valleys well for nasals, which in turn leads to better recognition accuracy.
{"title":"An improved chirp group delay based algorithm for estimating the vocal tract response","authors":"M. Jayesh, C. S. Ramalingam","doi":"10.5281/ZENODO.54522","DOIUrl":"https://doi.org/10.5281/ZENODO.54522","url":null,"abstract":"We propose a method for vocal tract estimation that is better than Bozkurt's chirp group delay method [1] and its zero-phase variant [2]. The chirp group delay method works only for voiced speech, is critically dependent on finding the glottal closure instants (GCI), deteriorates in performance when more than two pitch cycles are included for analysis, and does not work for unvoiced speech. The zero-phase variant eliminates these drawbacks but works poorly for nasal sounds. In our proposed method all outside-unit-circle zeros are reflected inside before computing the chirp group delay. The advantages are: (a) GCI knowledge not required, (b) the vocal tract estimate is far less sensitive to the location and duration of the analysis window, (c) works for unvoiced sounds, and (d) captures the spectral valleys well for nasals, which in turn leads to better recognition accuracy.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114069042","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：