This paper describes the application of the constellation based multiple model adaptive estimation (CBMMAE) algorithm to the identification and parameter estimation of nonlinear systems. The method was successfully applied to the identification of linear systems both stationary and nonstationary, being able to fine tune its parameters. The method starts by establishing a minimum set of models that are geometrically arranged in the space spanned by the unknown parameters, and adopts a strategy to adaptively update the constellation models in the parameter space in order to find the model resembling the system under identification. By downscaling the models parameters the constellation is shrunk, reducing the uncertainty of the parameters estimation. Simulations are presented to exhibit the application of the framework and the performance of the algorithm to the identification and parameters estimation of nonlinear systems.
{"title":"Nonlinear system identification using constellation based multiple model adaptive estimators","authors":"J. C. Martins, J. Caeiro, L. Sousa","doi":"10.5281/ZENODO.44203","DOIUrl":"https://doi.org/10.5281/ZENODO.44203","url":null,"abstract":"This paper describes the application of the constellation based multiple model adaptive estimation (CBMMAE) algorithm to the identification and parameter estimation of nonlinear systems. The method was successfully applied to the identification of linear systems both stationary and nonstationary, being able to fine tune its parameters. The method starts by establishing a minimum set of models that are geometrically arranged in the space spanned by the unknown parameters, and adopts a strategy to adaptively update the constellation models in the parameter space in order to find the model resembling the system under identification. By downscaling the models parameters the constellation is shrunk, reducing the uncertainty of the parameters estimation. Simulations are presented to exhibit the application of the framework and the performance of the algorithm to the identification and parameters estimation of nonlinear systems.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115621391","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}
This paper presents a novel approach to signal modeling for EEG signal rhythms. A new method of 3-stage DCT based multirate filterbank is proposed for the decomposition of EEG signals into brain rhythms: delta, theta, alpha, beta, and gamma rhythms. It is shown that theta, alpha, and gamma rhythms can be modeled as 1st order fractional Gaussian Noise (fGn), while the beta rhythms can be modeled as 2nd order fGn processes. These fGn processes are stationary random processes. Further, it is shown that the delta subband imbibes all the nonstationarity of EEG signals and can be modeled as a 1st order fractional Brownian motion (fBm) process. The modeling of subbands is characterized by Hurst exponent, estimated using maximum likelihood (ML) estimation method. The modeling approach has been tested on two public databases.
{"title":"Stochastic modeling of EEG rhythms with fractional Gaussian Noise","authors":"Mandar Karlekar, Anubha Gupta","doi":"10.5281/ZENODO.44212","DOIUrl":"https://doi.org/10.5281/ZENODO.44212","url":null,"abstract":"This paper presents a novel approach to signal modeling for EEG signal rhythms. A new method of 3-stage DCT based multirate filterbank is proposed for the decomposition of EEG signals into brain rhythms: delta, theta, alpha, beta, and gamma rhythms. It is shown that theta, alpha, and gamma rhythms can be modeled as 1st order fractional Gaussian Noise (fGn), while the beta rhythms can be modeled as 2nd order fGn processes. These fGn processes are stationary random processes. Further, it is shown that the delta subband imbibes all the nonstationarity of EEG signals and can be modeled as a 1st order fractional Brownian motion (fBm) process. The modeling of subbands is characterized by Hurst exponent, estimated using maximum likelihood (ML) estimation method. The modeling approach has been tested on two public databases.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114444626","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}
In this paper, the performance of generalised spatial modulation (GSM) and spatial modulation (SM) is studied assuming channel estimation errors (CSEs) and correlated Rayleigh and Rician fading channels. A new, simple, accurate and general analytical closed-form upper bound for the average bit error ratio (ABER) performance of both systems is derived. The analytical bound is shown to be applicable to correlated and uncorrelated channels, as well as to small and large scale multiple-input multiple-output (MIMO) systems. The results demonstrate that GSM is more suitable for large-scale MIMO systems than SM. The performance gain of GSM over SM is about 5 dB. The results also show that SM is very robust to CSEs. Specifically, the performance degradation of SM in the presence of CSEs are 0.7 dB and 0.3 dB for Rayleigh and Rician fading channels respectively. Lastly, the findings in this paper underpin the suitability of both GSM and SM for future large-scale MIMO systems.
{"title":"Generalised spatial modulation for large-scale MIMO","authors":"Abdelhamid Younis, R. Mesleh, M. Renzo, H. Haas","doi":"10.5281/ZENODO.44195","DOIUrl":"https://doi.org/10.5281/ZENODO.44195","url":null,"abstract":"In this paper, the performance of generalised spatial modulation (GSM) and spatial modulation (SM) is studied assuming channel estimation errors (CSEs) and correlated Rayleigh and Rician fading channels. A new, simple, accurate and general analytical closed-form upper bound for the average bit error ratio (ABER) performance of both systems is derived. The analytical bound is shown to be applicable to correlated and uncorrelated channels, as well as to small and large scale multiple-input multiple-output (MIMO) systems. The results demonstrate that GSM is more suitable for large-scale MIMO systems than SM. The performance gain of GSM over SM is about 5 dB. The results also show that SM is very robust to CSEs. Specifically, the performance degradation of SM in the presence of CSEs are 0.7 dB and 0.3 dB for Rayleigh and Rician fading channels respectively. Lastly, the findings in this paper underpin the suitability of both GSM and SM for future large-scale MIMO systems.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122145160","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. Kiayani, M. Abdelaziz, L. Anttila, V. Lehtinen, M. Valkama
In frequency division duplex transceivers employing non-contiguous carrier aggregation (CA) transmission, achieving sufficient isolation between transmit and receive chains using radio frequency filtering alone is increasingly difficult. Particularly challenging problem in this context is spurious intermodulation (IM) components due to nonlinear power amplifier (PA), which may easily overlap the receiver band. With realistic duplex filters, the residual spurious IM at RX band can be several dBs stronger than the thermal noise floor, leading to own receiver desensitization. In this paper, we carry out detailed signal modeling of spurious emissions due to wideband PAs at the third-order IM band. Stemming from this modeling, and using the known transmit data, we present an efficient nonlinear digital identification and cancellation technique to suppress the unwanted IM components at RX band. The proposed technique is verified with computer simulations, showing excellent calibration properties, hence relaxing filtering and duplexing distance requirements in spectrally-agile CA transceivers.
{"title":"DSP-based suppression of spurious emissions at RX band in carrier aggregation FDD transceivers","authors":"A. Kiayani, M. Abdelaziz, L. Anttila, V. Lehtinen, M. Valkama","doi":"10.5281/ZENODO.43795","DOIUrl":"https://doi.org/10.5281/ZENODO.43795","url":null,"abstract":"In frequency division duplex transceivers employing non-contiguous carrier aggregation (CA) transmission, achieving sufficient isolation between transmit and receive chains using radio frequency filtering alone is increasingly difficult. Particularly challenging problem in this context is spurious intermodulation (IM) components due to nonlinear power amplifier (PA), which may easily overlap the receiver band. With realistic duplex filters, the residual spurious IM at RX band can be several dBs stronger than the thermal noise floor, leading to own receiver desensitization. In this paper, we carry out detailed signal modeling of spurious emissions due to wideband PAs at the third-order IM band. Stemming from this modeling, and using the known transmit data, we present an efficient nonlinear digital identification and cancellation technique to suppress the unwanted IM components at RX band. The proposed technique is verified with computer simulations, showing excellent calibration properties, hence relaxing filtering and duplexing distance requirements in spectrally-agile CA transceivers.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126709476","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}
In this article we present a human motion detection frame-work, based on data derived from a single tri-axial accelerometer. The framework uses a set of different pre-processing methods that produce data representations which are respectively parameterized by statistical and physical features. These features are then concatenated and classified using well-known classification algorithms for the problem of motion recognition. Experimental evaluation was carried out according to a subject-dependent scenario, meaning that the classification is performed for each subject separately using their own data and the average accuracy for all individuals is computed. The best achieved detection performance for 14 everyday human motion activities, using the USC-HAD database, was approximately 95%. The results compare favorably are competitive to the best reported performance of 93.1% for the same database.
{"title":"Human motion detection in daily activity tasks using wearable sensors","authors":"Olga Politi, I. Mporas, V. Megalooikonomou","doi":"10.5281/ZENODO.44168","DOIUrl":"https://doi.org/10.5281/ZENODO.44168","url":null,"abstract":"In this article we present a human motion detection frame-work, based on data derived from a single tri-axial accelerometer. The framework uses a set of different pre-processing methods that produce data representations which are respectively parameterized by statistical and physical features. These features are then concatenated and classified using well-known classification algorithms for the problem of motion recognition. Experimental evaluation was carried out according to a subject-dependent scenario, meaning that the classification is performed for each subject separately using their own data and the average accuracy for all individuals is computed. The best achieved detection performance for 14 everyday human motion activities, using the USC-HAD database, was approximately 95%. The results compare favorably are competitive to the best reported performance of 93.1% for the same database.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129199469","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 assess the performance of Gaussianity tests, namely the Anscombe-Glynn, Lilliefors, Cramér-von Mises, and Giannakis-Tsatsanis (G-T), with the purpose of detecting narrowband and wideband interference in GNSS signals. Simulations have shown that the G-T test outperforms the others being suitable as a benchmark for comparison with different types of interference detection algorithms.
{"title":"Interference detection in GNSS signals using the Gaussianity criterion","authors":"F. Nunes, F. Sousa","doi":"10.5281/ZENODO.43827","DOIUrl":"https://doi.org/10.5281/ZENODO.43827","url":null,"abstract":"We assess the performance of Gaussianity tests, namely the Anscombe-Glynn, Lilliefors, Cramér-von Mises, and Giannakis-Tsatsanis (G-T), with the purpose of detecting narrowband and wideband interference in GNSS signals. Simulations have shown that the G-T test outperforms the others being suitable as a benchmark for comparison with different types of interference detection algorithms.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130570648","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}
In this paper, the set-theoretic based adaptive filtering task is studied for the case where the input signal is nonstationary and may assume relatively small values. Such a scenario is often faced in practice, with a notable application that of echo cancellation. It turns out that very small input values can trigger undesirable behaviour of the algorithm leading to severe performance fluctuations. The source of this malfunction is geometrically investigated and a solution complying with the set-theoretic philosophy is proposed. The new algorithm is evaluated in realistic echo-cancellation scenarios and compared with state-of-the-art methods for echo cancellation such as the IPNLMS and IPAPA algorithms.
{"title":"Sparsity-aware learning in the context of echo cancelation: A set theoretic estimation approach","authors":"Y. Kopsinis, S. Chouvardas, S. Theodoridis","doi":"10.5281/ZENODO.44190","DOIUrl":"https://doi.org/10.5281/ZENODO.44190","url":null,"abstract":"In this paper, the set-theoretic based adaptive filtering task is studied for the case where the input signal is nonstationary and may assume relatively small values. Such a scenario is often faced in practice, with a notable application that of echo cancellation. It turns out that very small input values can trigger undesirable behaviour of the algorithm leading to severe performance fluctuations. The source of this malfunction is geometrically investigated and a solution complying with the set-theoretic philosophy is proposed. The new algorithm is evaluated in realistic echo-cancellation scenarios and compared with state-of-the-art methods for echo cancellation such as the IPNLMS and IPAPA algorithms.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121955666","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}
This paper investigates the effect of MPEG audio compression on HMM-based speech synthesis using two state-of-the-art vocoders. Speech signals are first encoded with various compression rates and analyzed using the GlottHMM and STRAIGHT vocoders. Objective evaluation results show that the parameters of both vocoders gradually degrade with increasing compression rates, but with a clear increase in degradation with bit-rates of 32 kbit/s or less. Experiments with HMM-based synthesis with the two vocoders show that the degradation in quality is already perceptible with bit-rates of 32 kbit/s and both vocoders show similar trend in degradation with respect to compression ratio. The most perceptible artefacts induced by the compression are spectral distortion and reduced bandwidth, while prosody is better preserved.
{"title":"Effect of MPEG audio compression on vocoders used in statistical parametric speech synthesis","authors":"B. Bollepalli, T. Raitio","doi":"10.5281/ZENODO.43781","DOIUrl":"https://doi.org/10.5281/ZENODO.43781","url":null,"abstract":"This paper investigates the effect of MPEG audio compression on HMM-based speech synthesis using two state-of-the-art vocoders. Speech signals are first encoded with various compression rates and analyzed using the GlottHMM and STRAIGHT vocoders. Objective evaluation results show that the parameters of both vocoders gradually degrade with increasing compression rates, but with a clear increase in degradation with bit-rates of 32 kbit/s or less. Experiments with HMM-based synthesis with the two vocoders show that the degradation in quality is already perceptible with bit-rates of 32 kbit/s and both vocoders show similar trend in degradation with respect to compression ratio. The most perceptible artefacts induced by the compression are spectral distortion and reduced bandwidth, while prosody is better preserved.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128198409","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}
Filter design is a fundamental problem in signal processing and important in many applications. In this paper we consider a communication application with spectral constraints, using filter designs that can be solved globally via convex optimization. Tradeoffs are discussed in order to determine which design is the most appropriate, and for these applications, finite impulse response filters appear to be more suitable than infinite impulse response filters since they allow for more flexible objective functions, shorter transients, and faster filter implementations.
{"title":"Filter design with hard spectral constraints","authors":"J. Karlsson, Jian Li, P. Stoica","doi":"10.5281/ZENODO.43852","DOIUrl":"https://doi.org/10.5281/ZENODO.43852","url":null,"abstract":"Filter design is a fundamental problem in signal processing and important in many applications. In this paper we consider a communication application with spectral constraints, using filter designs that can be solved globally via convex optimization. Tradeoffs are discussed in order to determine which design is the most appropriate, and for these applications, finite impulse response filters appear to be more suitable than infinite impulse response filters since they allow for more flexible objective functions, shorter transients, and faster filter implementations.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115829449","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}
Biometric systems are vulnerable to the diverse attacks that emerged as a challenge to assure the reliability in adopting these systems in real-life scenario. In this work, we propose a novel solution to detect a presentation attack based on exploring both statistical and Cepstral features. The proposed Presentation Attack Detection (PAD) algorithm will extract the statistical features that can capture the micro-texture variation using Binarized Statistical Image Features (BSIF) and Cepstral features that can reflect the micro changes in frequency using 2D Cepstrum analysis. We then fuse these features to form a single feature vector before making a decision on whether a capture attempt is a normal presentation or an artefact presentation using linear Support Vector Machine (SVM). Extensive experiments carried out on a publicly available face and iris spoof database show the efficacy of the proposed PAD algorithm with an Average Classification Error Rate (ACER) = 10.21% on face and ACER = 0% on the iris biometrics.
{"title":"Presentation attack detection algorithm for face and iris biometrics","authors":"Ramachandra Raghavendra, C. Busch","doi":"10.5281/ZENODO.43982","DOIUrl":"https://doi.org/10.5281/ZENODO.43982","url":null,"abstract":"Biometric systems are vulnerable to the diverse attacks that emerged as a challenge to assure the reliability in adopting these systems in real-life scenario. In this work, we propose a novel solution to detect a presentation attack based on exploring both statistical and Cepstral features. The proposed Presentation Attack Detection (PAD) algorithm will extract the statistical features that can capture the micro-texture variation using Binarized Statistical Image Features (BSIF) and Cepstral features that can reflect the micro changes in frequency using 2D Cepstrum analysis. We then fuse these features to form a single feature vector before making a decision on whether a capture attempt is a normal presentation or an artefact presentation using linear Support Vector Machine (SVM). Extensive experiments carried out on a publicly available face and iris spoof database show the efficacy of the proposed PAD algorithm with an Average Classification Error Rate (ACER) = 10.21% on face and ACER = 0% on the iris biometrics.","PeriodicalId":198408,"journal":{"name":"2014 22nd European Signal Processing Conference (EUSIPCO)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133271159","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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