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IEEE Seventh SP Workshop on Statistical Signal and Array Processing最新文献

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Analysis and Interpretation of the Reduced-Rank Generalized Likelihood-Ratio Test 约秩广义似然比检验的分析与解释
IEEE Seventh SP Workshop on Statistical Signal and Array Processing Pub Date : 1994-06-26 DOI: 10.1109/SSAP.1994.572436
I. Kirsteins
{"title":"Analysis and Interpretation of the Reduced-Rank Generalized Likelihood-Ratio Test","authors":"I. Kirsteins","doi":"10.1109/SSAP.1994.572436","DOIUrl":"https://doi.org/10.1109/SSAP.1994.572436","url":null,"abstract":"An analysis and interpretation of the reduced-rank generalized likelihood-ratio test (RR-GLRT) detector is presented in this paper. First, simple and accurate approximations to the RR-GLRT test statistics are derived. The approximations are verified by computer simulation and are shown to be accurate over a wide range of interference and signal levels These approximation are then used to show that the RR-GLRT is related to the UMP invariant test and to calculate the moments and deflection of the RR-GLRT statistic.","PeriodicalId":151571,"journal":{"name":"IEEE Seventh SP Workshop on Statistical Signal and Array Processing","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114836786","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}
引用次数: 1
Robust Spectral-Based Techniques for Classification of Wldeband Transient Signals 基于鲁棒谱的宽带暂态信号分类技术
IEEE Seventh SP Workshop on Statistical Signal and Array Processing Pub Date : 1994-06-26 DOI: 10.1109/SSAP.1994.572522
M. Fargues, R. Hippenstiel
{"title":"Robust Spectral-Based Techniques for Classification of Wldeband Transient Signals","authors":"M. Fargues, R. Hippenstiel","doi":"10.1109/SSAP.1994.572522","DOIUrl":"https://doi.org/10.1109/SSAP.1994.572522","url":null,"abstract":"We recently investigated various spectral-based classification schemes designed to separate wideband transient signals and compared their performances to those obtained using a back-propagation neural network implementation [2]. The spectral-based measures considered include the Bhattacharyya distance, the divergence, the normalized cross-correlation coefficient, and the modified normalized cross-correlation coefficient. Results showed that accurate classification may be obtained using spectral-based measures and that the performances compare, or are sometimes better, to those obtained using neural networks when the training data used to train the neural network is small. In this paper we investigate the robustness of the spectral measures and the neural network approximation classification schemes to white additive noise degradation in the testing sets. Results show that the spectral-based techniques are more robust when the testing sets are degraded with noise.","PeriodicalId":151571,"journal":{"name":"IEEE Seventh SP Workshop on Statistical Signal and Array Processing","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116744134","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}
引用次数: 0
A New Cumulant Based Phase Estimation Nonminimum-phase Systems By Allpass 一种新的基于累积量的相位估计非最小相位系统
IEEE Seventh SP Workshop on Statistical Signal and Array Processing Pub Date : 1994-06-26 DOI: 10.1109/SSAP.1994.572486
Huang-Lin Yang, Chong-Yung Chi
{"title":"A New Cumulant Based Phase Estimation Nonminimum-phase Systems By Allpass","authors":"Huang-Lin Yang, Chong-Yung Chi","doi":"10.1109/SSAP.1994.572486","DOIUrl":"https://doi.org/10.1109/SSAP.1994.572486","url":null,"abstract":"This paper presents a new cumulant based phase estimation method for linear time-invariant (LTI) systems with only non-Gaussian measurements contaminated by Gaussian noise. An optimum allpass filter is designed to process the given measurements such that its output has a maximum Mth-order (2 3) cumulant in absolute value. It can be shown that the system phase is equivalent to the negative value of the optimum allpass filter phase except for a linear phase factor. Some simulation results are provided to support the proposed phase estimation method.","PeriodicalId":151571,"journal":{"name":"IEEE Seventh SP Workshop on Statistical Signal and Array Processing","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114215427","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}
引用次数: 1
Mechanical Vibration Analysis Using an Optical Sensor 利用光学传感器进行机械振动分析
IEEE Seventh SP Workshop on Statistical Signal and Array Processing Pub Date : 1994-06-26 DOI: 10.1109/SSAP.1994.572534
F. Claveau, S. Lord, D. Gingras, P. Fortier
{"title":"Mechanical Vibration Analysis Using an Optical Sensor","authors":"F. Claveau, S. Lord, D. Gingras, P. Fortier","doi":"10.1109/SSAP.1994.572534","DOIUrl":"https://doi.org/10.1109/SSAP.1994.572534","url":null,"abstract":"A laser-based contactless displacement measurement system developed at the National Optics Institute is used for data acquisition to analyze the mechanical vibrations exhibited by vibrating structures and machines. The analysis of these vibrations requires a number of signal processing operations which include the determination of the system conditions through a classification of various observed vibration signatures and the detection of changes in the vibration signature in order to identify possible trends. This information is also combined with the physical characteristics and contextual data (operating mode, etc.) of the system under surveillance to allow the evaluation of certain characteristics like fatigue, abnormal stress, life span, etc., resulting in a high level classification of mechanical behaviours and structural faults according to the type of application. The aim of this paper is to introduce the problem, the instrumentation, and the requirements in terms of statistical signal processing.","PeriodicalId":151571,"journal":{"name":"IEEE Seventh SP Workshop on Statistical Signal and Array Processing","volume":"EM-33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126528228","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}
引用次数: 7
Multiwindow Post-Doppler Space-Time Adaptive Processing 多窗口后多普勒时空自适应处理
IEEE Seventh SP Workshop on Statistical Signal and Array Processing Pub Date : 1994-06-26 DOI: 10.1109/SSAP.1994.572543
J. Ward, A. Steinhardt
{"title":"Multiwindow Post-Doppler Space-Time Adaptive Processing","authors":"J. Ward, A. Steinhardt","doi":"10.1109/SSAP.1994.572543","DOIUrl":"https://doi.org/10.1109/SSAP.1994.572543","url":null,"abstract":"Advanced airborne radars must perform target detection in the presence of interference and heavy clutter, Space-time adaptive processing (STAP) refers to a class of adaptive filtering techniques that simultaneously rocess the spatial signals from an antenna .array and d e temporal signals from multiple pulses an order to suppress both jammin and clutter. A reduceddimension suboptimum STh' architecture utilizing multi le dop ler filter banks on each element is suggestel Digrent methods for choosing the doppler filters are considered and a condition which yields minimum clutter r a d is derived. PRI-staggered postdop ler meets the condition and rovides both ezcellent per6rmance with few degrees orfreedom and the abili t y to maintain low adapted doppler sadelobes. Adjacent bin post-doppler re uires more de rees of freedom when low doppler sidelo%es are desire!","PeriodicalId":151571,"journal":{"name":"IEEE Seventh SP Workshop on Statistical Signal and Array Processing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125628763","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}
引用次数: 21
Adaptive Beamforming for Slow Fading Rayleigh Signals 慢衰落瑞利信号的自适应波束形成
IEEE Seventh SP Workshop on Statistical Signal and Array Processing Pub Date : 1994-06-26 DOI: 10.1109/SSAP.1994.572471
R. DeLap, A. Hero
{"title":"Adaptive Beamforming for Slow Fading Rayleigh Signals","authors":"R. DeLap, A. Hero","doi":"10.1109/SSAP.1994.572471","DOIUrl":"https://doi.org/10.1109/SSAP.1994.572471","url":null,"abstract":"In this paper we develop an adaptive beamsummer for direction of arrival (DOA) estimation of slow fading Raleigh signals, using a new design approach, termed \"Adaptive Detection/Estimation for specific Tasks\" (ADEPT). For DOA estimation, the ADEPT method yields a weight adaptation criterion which is optimized for those weights that minimize the Cramer-Rao (CR) lower bound on achievable mean-square-error of any unbiased DOA estimator constructed on the beamsummer outputs. Simulation results are provided which show that the ADEPT DOA beamsummer yields DOA estimates whose meansquared error (MSE) approaches that of the more complex maximum likelihood implementation.","PeriodicalId":151571,"journal":{"name":"IEEE Seventh SP Workshop on Statistical Signal and Array Processing","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123064792","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}
引用次数: 0
Variable Frame Length Of A Higher Order Speech AR Estimation In A Speech Enhancement System 语音增强系统中高阶语音AR估计的可变帧长
IEEE Seventh SP Workshop on Statistical Signal and Array Processing Pub Date : 1994-06-26 DOI: 10.1109/SSAP.1994.572483
J. M. Salavedra, E. Masgrau, A. Moreno, J. Estarellas
{"title":"Variable Frame Length Of A Higher Order Speech AR Estimation In A Speech Enhancement System","authors":"J. M. Salavedra, E. Masgrau, A. Moreno, J. Estarellas","doi":"10.1109/SSAP.1994.572483","DOIUrl":"https://doi.org/10.1109/SSAP.1994.572483","url":null,"abstract":"We study some speech enhancement algorithms based on the iterative Wiener filtering method due to Lim-Oppenheim [2], where the AR spectral estimation of the speech is carried out using a 2nd-order analysis. But in our algorithms we consider an AR estimation by means of cumulant analysis. This work extends some preceding papers due to the authors, providing a different frame length where AR estimation is done. Information of previous speech frames is used to initiate speech AR modelling of the current frame. Two parameters are introduced to dessign Wiener filter at first iteration of this iterative algorithm. These parameters are the Interframe Factor IF and the Previous Frame Iteration PFI. They allow a very important noise suppression after processing only fxst iteration of this algorithm, without any appreciable increase of distortion.","PeriodicalId":151571,"journal":{"name":"IEEE Seventh SP Workshop on Statistical Signal and Array Processing","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134434928","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}
引用次数: 1
Multisensor Automatic Target Classification with Neural Networks 基于神经网络的多传感器目标自动分类
IEEE Seventh SP Workshop on Statistical Signal and Array Processing Pub Date : 1994-06-26 DOI: 10.1109/SSAP.1994.572531
Fengzhen Wang, T. Lo, J. Litva, É. Bossé
{"title":"Multisensor Automatic Target Classification with Neural Networks","authors":"Fengzhen Wang, T. Lo, J. Litva, É. Bossé","doi":"10.1109/SSAP.1994.572531","DOIUrl":"https://doi.org/10.1109/SSAP.1994.572531","url":null,"abstract":"This paper presents the multisensor data fusion for airborne target classification with artificial neural network. A feature set, which possesses the dominant characteristics of targets and has a certain dynamic range, is chosen. The entire system consists of identification nets (IN) and classification net (CN). Each identification network is used to extract a particular feature of the target, then the outputs of identification networks are fused by classification network, in which the neural network acts as a decision making processor. In the paper, multilayer perceptrons neural networks trained by back-propagation (BP) rule are discussed. In order to speed up the training or decrease the number of epoch in learning process, both momentum and adaptive learning rate methods are used. The simulation results show that the technique of automatic target classification using neural networks can achieve robust decision performance.","PeriodicalId":151571,"journal":{"name":"IEEE Seventh SP Workshop on Statistical Signal and Array Processing","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127582586","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}
引用次数: 0
Properties of the Evolutionary Maximum Entropy Spectral Estimator 演化最大熵谱估计器的性质
IEEE Seventh SP Workshop on Statistical Signal and Array Processing Pub Date : 1994-06-26 DOI: 10.1109/SSAP.1994.572494
S.I. Shah, L. Chaparro, A. El-Jaroudi
{"title":"Properties of the Evolutionary Maximum Entropy Spectral Estimator","authors":"S.I. Shah, L. Chaparro, A. El-Jaroudi","doi":"10.1109/SSAP.1994.572494","DOIUrl":"https://doi.org/10.1109/SSAP.1994.572494","url":null,"abstract":"2. EVOLUTIONARY MAXIMUM ENTROPY ESTIMATION Using maximum entropy spectral analysis and the theThe Wold-Cramer representation [4] of a non-stationary by considering it the output of a linear timevarying system (LTV) with white noise as input: ory of the Wold-Cramer evolutionary spectrum we develop signal is the evolutionary maximum entropy @ME) estimator for non-stationary signals. The EME estimation reduces to the fitting of a time-varying autoregressive model to the Fourier coefficients of the evolutionary spectrum. The model parameters are efficientlv found bv means of the Levinson alH(n, w)ejwndZ(w) (1) gorithm. Just as in the stationary case, the EME estimator provides very good frequency resolution and can be used to obtain autoregressive models. In this paper, we present the EME estimator and discuss some of its properties. Our aim is to show that the EME estimator has analogous properties to the classical ME estimator for stationary signals.","PeriodicalId":151571,"journal":{"name":"IEEE Seventh SP Workshop on Statistical Signal and Array Processing","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127498361","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}
引用次数: 1
A Monte-Carlo Method for Locally Optimal Quantized Merging of Correlated Detection Statistics 相关检测统计量局部最优量化合并的蒙特卡罗方法
IEEE Seventh SP Workshop on Statistical Signal and Array Processing Pub Date : 1994-06-26 DOI: 10.1109/SSAP.1994.572430
D. Abraham
{"title":"A Monte-Carlo Method for Locally Optimal Quantized Merging of Correlated Detection Statistics","authors":"D. Abraham","doi":"10.1109/SSAP.1994.572430","DOIUrl":"https://doi.org/10.1109/SSAP.1994.572430","url":null,"abstract":"In the detection of unknown deterministic signals in noise, consideration may be restricted to statistics that are sufficient for detection of certain classes of signals. Here, the case of correlated statistics that are assumed to have analytically intractable probability distributions is considered. A locally optimal quantized detector that merges the multivariate sufficient statistics is proposed. Quantization is required for implementation, which utilizes a Monte-Carlo evaluation of the levels minimizing the mean squared error for a specific partitioning of the range space of the sufficient statistics. Performance improvement over the individual statistics and a test using the maximum of the individual statistics is illustrated with an example.","PeriodicalId":151571,"journal":{"name":"IEEE Seventh SP Workshop on Statistical Signal and Array Processing","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124922762","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}
引用次数: 0
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