Two new radar signal models using nonlinear frequency modulation are proposed and investigated with respect to enhancing the target's range estimation and reducing the sidelobe level. The performance of the proposed signal models is compared to the currently popular linear and nonlinear frequency modulation signal models. The Cramer Rao Lower Bound along with main lobe width and the peak to sidelobe ratio are used for comparing the signal models to show that better range accuracy and smaller sidelobes can be achieved with the proposed signal models.
{"title":"Novel radar signal models using nonlinear frequency modulation","authors":"Sebastian Alphonse, G. Williamson","doi":"10.5281/ZENODO.44184","DOIUrl":"https://doi.org/10.5281/ZENODO.44184","url":null,"abstract":"Two new radar signal models using nonlinear frequency modulation are proposed and investigated with respect to enhancing the target's range estimation and reducing the sidelobe level. The performance of the proposed signal models is compared to the currently popular linear and nonlinear frequency modulation signal models. The Cramer Rao Lower Bound along with main lobe width and the peak to sidelobe ratio are used for comparing the signal models to show that better range accuracy and smaller sidelobes can be achieved with the proposed signal models.","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":"123143499","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 addresses the problem of retrieving those shots from a database of video sequences that match a query image. Existing architectures match the images using a high-level representation of local features extracted from the video database, and are mainly based on Bag ofWords model. Such architectures lack however the capability to scale up to very large databases. Recently, Fisher Vectors showed promising results in large scale image retrieval problems, but it is still not clear how they can be best exploited in video-related applications. In our work, we use compressed Fisher Vectors to represent the video shots and we show that inherent correlation between video frames can be effectively exploited. Experiments show that our proposed system achieves better performance while having lower computational requirements than similar architectures.
本文解决了从与查询图像匹配的视频序列数据库中检索这些镜头的问题。现有的体系结构主要基于Bag of words模型，使用从视频数据库中提取的局部特征的高级表示来匹配图像。然而，这种架构缺乏扩展到非常大的数据库的能力。最近，Fisher Vectors在大规模图像检索问题上显示了有希望的结果，但如何在视频相关应用中最好地利用它们仍然不清楚。在我们的工作中，我们使用压缩的Fisher向量来表示视频镜头，我们表明视频帧之间的内在相关性可以有效地利用。实验表明，与同类体系结构相比，我们的系统具有更好的性能和更低的计算需求。
{"title":"Shot-based object retrieval from video with compressed Fisher Vectors","authors":"Luca Bertinetto, A. Fiandrotti, E. Magli","doi":"10.5281/ZENODO.44154","DOIUrl":"https://doi.org/10.5281/ZENODO.44154","url":null,"abstract":"This paper addresses the problem of retrieving those shots from a database of video sequences that match a query image. Existing architectures match the images using a high-level representation of local features extracted from the video database, and are mainly based on Bag ofWords model. Such architectures lack however the capability to scale up to very large databases. Recently, Fisher Vectors showed promising results in large scale image retrieval problems, but it is still not clear how they can be best exploited in video-related applications. In our work, we use compressed Fisher Vectors to represent the video shots and we show that inherent correlation between video frames can be effectively exploited. Experiments show that our proposed system achieves better performance while having lower computational requirements than similar architectures.","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":"120904471","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}
The subspace-based line detection (SLIDE) algorithm enables the estimation of parameters of multiple lines within a digital image by mapping these lines to frequency modulated (FM) signals. In this paper, we consider the estimation of such obtained FM signals by using estimators developed for polynomial-phase signals (PPSs). For this purpose, a recently proposed method that combines the cubic phase function (CPF) and high-order ambiguity function (HAF), referred to as the product CPF-HAF (PCPF-HAF), has been used. Simulations show that the PCPF-HAF-based estimator is more accurate than the estimators based on time-frequency representations.
{"title":"Parametric estimation of multi-line parameters based on slide algorithm","authors":"S. Djukanović, M. Simeunović, I. Djurović","doi":"10.5281/ZENODO.44206","DOIUrl":"https://doi.org/10.5281/ZENODO.44206","url":null,"abstract":"The subspace-based line detection (SLIDE) algorithm enables the estimation of parameters of multiple lines within a digital image by mapping these lines to frequency modulated (FM) signals. In this paper, we consider the estimation of such obtained FM signals by using estimators developed for polynomial-phase signals (PPSs). For this purpose, a recently proposed method that combines the cubic phase function (CPF) and high-order ambiguity function (HAF), referred to as the product CPF-HAF (PCPF-HAF), has been used. Simulations show that the PCPF-HAF-based estimator is more accurate than the estimators based on time-frequency representations.","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":"115403063","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}
Hossein Asgharimoghaddam, Antti Tölli, Nandana Rajatheva
The optimal decentralization of multi-cell minimum power beamforming requires exchange of terms related to instantaneous inter-cell interference (ICI) values or channel state information (CSI) via a backhaul link. This limits the achievable performance in the limited backhaul capacity scenarios, especially when dealing with a fast fading scenario or a large number of users and antennas. In this work, we utilize the results from random matrix theory for developing two algorithms based on uplink-downlink duality and optimization decomposition relying on limited cooperation between nodes to share knowledge about channel statistics. As a result, approximately optimal power allocations are achieved based on statistics of the channels with greatly reduced backhaul information exchange rate. The simulations show that the performance gap due to the approximations is small even when the problem dimensions are relatively small.
{"title":"Decentralized multi-cell beamforming via large system analysis in correlated channels","authors":"Hossein Asgharimoghaddam, Antti Tölli, Nandana Rajatheva","doi":"10.5281/ZENODO.54496","DOIUrl":"https://doi.org/10.5281/ZENODO.54496","url":null,"abstract":"The optimal decentralization of multi-cell minimum power beamforming requires exchange of terms related to instantaneous inter-cell interference (ICI) values or channel state information (CSI) via a backhaul link. This limits the achievable performance in the limited backhaul capacity scenarios, especially when dealing with a fast fading scenario or a large number of users and antennas. In this work, we utilize the results from random matrix theory for developing two algorithms based on uplink-downlink duality and optimization decomposition relying on limited cooperation between nodes to share knowledge about channel statistics. As a result, approximately optimal power allocations are achieved based on statistics of the channels with greatly reduced backhaul information exchange rate. The simulations show that the performance gap due to the approximations is small even when the problem dimensions are relatively small.","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":"132475813","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 we present a speech representation based on the Linear Predictive Coding of the Zero Phase version of the signal (ZP-LPC) and its robustness in presence of additive noise for robust formant estimation. Two representations are proposed for using in the frequency candidate proposition stage of the formant tracking algorithm: 1) the roots of ZP-LPC and 2) the peaks of its group delay function (GDF). Both of them are studied and evaluated in noisy environments with a synthetic dataset to demonstrate their robustness. Proposed representations are then used in a formant tracking experiment with a speech database. A beam search algorithm is used for selecting the best candidates as formant. Results show that our method outperforms related techniques in noisy test configurations and is a good fit for use in applications that have to work in noisy environments.
{"title":"Zero Phase speech representation for robust formant tracking","authors":"D. González, EDUARDO LLEIDA SOLANO, J. Lara","doi":"10.5281/ZENODO.43808","DOIUrl":"https://doi.org/10.5281/ZENODO.43808","url":null,"abstract":"In this paper we present a speech representation based on the Linear Predictive Coding of the Zero Phase version of the signal (ZP-LPC) and its robustness in presence of additive noise for robust formant estimation. Two representations are proposed for using in the frequency candidate proposition stage of the formant tracking algorithm: 1) the roots of ZP-LPC and 2) the peaks of its group delay function (GDF). Both of them are studied and evaluated in noisy environments with a synthetic dataset to demonstrate their robustness. Proposed representations are then used in a formant tracking experiment with a speech database. A beam search algorithm is used for selecting the best candidates as formant. Results show that our method outperforms related techniques in noisy test configurations and is a good fit for use in applications that have to work in noisy environments.","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":"130880612","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 consider the problem of modelling asymmetric near-Gaussian correlated signals by autoregressive models with epsilon-skew normal innovations. Moments and maximum likelihood estimators of the parameters are proposed and their limit distributions are derived. Monte Carlo simulation results are analyzed and the model is fitted to a real time series.
{"title":"Autoregressive models with epsilon-skew-normal innovations","authors":"P. Bondon","doi":"10.5281/ZENODO.44204","DOIUrl":"https://doi.org/10.5281/ZENODO.44204","url":null,"abstract":"We consider the problem of modelling asymmetric near-Gaussian correlated signals by autoregressive models with epsilon-skew normal innovations. Moments and maximum likelihood estimators of the parameters are proposed and their limit distributions are derived. Monte Carlo simulation results are analyzed and the model is fitted to a real time series.","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":"131387807","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}
Randomized coordinate descent (RCD), attractive for its robustness and ability to cope with large scale problems, is here investigated for the first time in an adaptive context. We present an RCD adaptive algorithm for finding sparse least-squares solutions to linear systems, in particular for FIR channel identification. The algorithm has low and tunable complexity and, as a special feature, adapts the probabilities with which the coordinates are chosen at each time moment. We show through simulation that the algorithm has tracking properties near those of the best current methods and investigate the trade-offs in the choices of the parameters.
{"title":"Adaptive randomized coordinate descent for solving sparse systems","authors":"Alexandru Onose, B. Dumitrescu","doi":"10.5281/ZENODO.43866","DOIUrl":"https://doi.org/10.5281/ZENODO.43866","url":null,"abstract":"Randomized coordinate descent (RCD), attractive for its robustness and ability to cope with large scale problems, is here investigated for the first time in an adaptive context. We present an RCD adaptive algorithm for finding sparse least-squares solutions to linear systems, in particular for FIR channel identification. The algorithm has low and tunable complexity and, as a special feature, adapts the probabilities with which the coordinates are chosen at each time moment. We show through simulation that the algorithm has tracking properties near those of the best current methods and investigate the trade-offs in the choices of the parameters.","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":"124609134","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 proposes a quantization parameter estimation algorithm for HEVC CTU rate control. Several methods were proposed, mostly based on Lagrangian optimization combined with Laplacian distribution for transformed coefficients. These methods are accurate but increase the encoder complexity. This paper provides an innovative reduced complexity algorithm based on a ρ-domain rate model. Indeed, for each CTU, the algorithm predicts encoding parameters based on co-located CTU. By combining it with Laplacian distribution for transformed coefficients, we obtain the dead-zone boundary for quantization and the related quantization parameter. Experiments in the HEVC HM Reference Software show a good accuracy with only a 3% average bitrate error and no PSNR deterioration for random-access configuration.
{"title":"Efficient quantization parameter estimation in HEVC based on ρ-domain","authors":"T. Biatek, M. Raulet, J. Travers, O. Déforges","doi":"10.5281/ZENODO.44153","DOIUrl":"https://doi.org/10.5281/ZENODO.44153","url":null,"abstract":"This paper proposes a quantization parameter estimation algorithm for HEVC CTU rate control. Several methods were proposed, mostly based on Lagrangian optimization combined with Laplacian distribution for transformed coefficients. These methods are accurate but increase the encoder complexity. This paper provides an innovative reduced complexity algorithm based on a ρ-domain rate model. Indeed, for each CTU, the algorithm predicts encoding parameters based on co-located CTU. By combining it with Laplacian distribution for transformed coefficients, we obtain the dead-zone boundary for quantization and the related quantization parameter. Experiments in the HEVC HM Reference Software show a good accuracy with only a 3% average bitrate error and no PSNR deterioration for random-access configuration.","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":"131327163","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}
Abderrahim Halimi, C. Mailhes, J. Tourneret, T. Moreau, F. Boy
Delay/Doppler radar altimetry is a new technology that has been receiving an increasing interest, especially since the launch of Cryosat-2 in 2010, the first altimeter using this technique. The Delay/Doppler technique aims at reducing the measurement noise and increasing the along-track resolution in comparison with conventional pulse limited altimetry. A new semi-analytical model with five parameters has been recently introduced for this new technology. However, two of these parameters are highly correlated resulting in bad estimation performance when estimating all parameters. This paper proposes a new strategy improving estimation performance for delay/Doppler altimetry. The proposed strategy exploits all the information contained in the delay/Doppler domain. A comparison with other classical algorithms (using the temporal samples only) allows to appreciate the gain in estimation performance obtained when using both temporal and Doppler data.
{"title":"Exploiting time and frequency information for Delay/Doppler altimetry","authors":"Abderrahim Halimi, C. Mailhes, J. Tourneret, T. Moreau, F. Boy","doi":"10.5281/ZENODO.43918","DOIUrl":"https://doi.org/10.5281/ZENODO.43918","url":null,"abstract":"Delay/Doppler radar altimetry is a new technology that has been receiving an increasing interest, especially since the launch of Cryosat-2 in 2010, the first altimeter using this technique. The Delay/Doppler technique aims at reducing the measurement noise and increasing the along-track resolution in comparison with conventional pulse limited altimetry. A new semi-analytical model with five parameters has been recently introduced for this new technology. However, two of these parameters are highly correlated resulting in bad estimation performance when estimating all parameters. This paper proposes a new strategy improving estimation performance for delay/Doppler altimetry. The proposed strategy exploits all the information contained in the delay/Doppler domain. A comparison with other classical algorithms (using the temporal samples only) allows to appreciate the gain in estimation performance obtained when using both temporal and Doppler data.","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":"114277917","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}
Speech enhancement approaches are often enhanced by speech presence probability (SPP) estimation. However, SPP estimators suffer from random fluctuations of the a posteriori signal-to-noise ratio (SNR). While there exist proposals that overcome the random fluctuations by basing the SPP framework on smoothed observations, these approaches do not take into account the super-Gaussian nature of speech signals. Thus, in this paper we define a framework that allows for modeling the likelihoods of speech presence for smoothed observations, while at the same time assuming super-Gaussian speech coefficients. The proposed approach is shown to outperform the reference approaches in terms of the amount of noise leakage and the amount of musical noise.
{"title":"A speech presence probability estimator based on fixed priors and a heavy-tailed speech model","authors":"Balázs Fodor, Timo Gerkmann","doi":"10.5281/ZENODO.43797","DOIUrl":"https://doi.org/10.5281/ZENODO.43797","url":null,"abstract":"Speech enhancement approaches are often enhanced by speech presence probability (SPP) estimation. However, SPP estimators suffer from random fluctuations of the a posteriori signal-to-noise ratio (SNR). While there exist proposals that overcome the random fluctuations by basing the SPP framework on smoothed observations, these approaches do not take into account the super-Gaussian nature of speech signals. Thus, in this paper we define a framework that allows for modeling the likelihoods of speech presence for smoothed observations, while at the same time assuming super-Gaussian speech coefficients. The proposed approach is shown to outperform the reference approaches in terms of the amount of noise leakage and the amount of musical noise.","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":"114764394","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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