2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA)最新文献_第2页

Automatic identification of electrical appliances using smart plugs 使用智能插头自动识别电器

2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA) Pub Date : 2013-05-12 DOI: 10.1109/WOSSPA.2013.6602380

A. Ridi, Christophe Gisler, J. Hennebert

引用次数: 47

An effective segmentation of moving objects by a novel local regions-based level set 一种新的基于局部区域的水平集对运动目标的有效分割

2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA) Pub Date : 2013-05-12 DOI: 10.1109/WOSSPA.2013.6602360

M. Boumehed, B. Alshaqaqi, A. Ouamri, M. Keche, Mohamed El Amine Ouis

引用次数: 0

Relay self interference minimisation using tapped filter 继电器自干扰最小化使用抽头滤波器

2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA) Pub Date : 2013-05-12 DOI: 10.1109/WOSSPA.2013.6602383

S. Al-Jazzar, T. Al-Naffouri

{"title":"Relay self interference minimisation using tapped filter","authors":"S. Al-Jazzar, T. Al-Naffouri","doi":"10.1109/WOSSPA.2013.6602383","DOIUrl":"https://doi.org/10.1109/WOSSPA.2013.6602383","url":null,"abstract":"In this paper we introduce a self interference (SI) estimation and minimisation technique for amplify and forward relays. Relays are used to help forward signals between a transmitter and a receiver. This helps increase the signal coverage and reduce the required transmitted signal power. One problem that faces relays communications is the leaked signal from the relay's output to its input. This will cause an SI problem where the new received signal at the relay's input will be added with the unwanted leaked signal from the relay's output. A Solution is proposed in this paper to estimate and minimise this SI which is based upon using a tapped filter at the destination. To get the optimum weights for this tapped filter, some channel parameters must be estimated first. This is performed blindly at the destination without the need of any training. This channel parameter estimation method is named the blind-self-interference-channel-estimation (BSICE) method. The next step in the proposed solution is to estimate the tapped filter's weights. This is performed by minimising the mean squared error (MSE) at the destination. This proposed method is named the MSE-Optimum Weight (MSE-OW) method. Simulation results are provided in this paper to verify the performance of BSICE and MSE-OW methods.","PeriodicalId":417940,"journal":{"name":"2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114120395","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: 2

BEMD-Unsharp Masking for retinal angiography image sharpening 用于视网膜血管造影图像锐化的bemd -非锐化掩蔽

2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA) Pub Date : 2013-05-12 DOI: 10.1109/WOSSPA.2013.6602365

B. Bouledjfane, L. Bennacer, M. Kahli

引用次数: 2

Mathematical models for machine learning and pattern recognition 机器学习和模式识别的数学模型

2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA) Pub Date : 2013-05-12 DOI: 10.1109/WOSSPA.2013.6602331

D. Bouchoffra, F. Ykhlef

引用次数: 2

Flexible OFDM system for peak power reduction in OFDM-based Cognitive Radio context 基于认知无线电环境下OFDM峰值功率降低的柔性OFDM系统

2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA) Pub Date : 2013-05-12 DOI: 10.1109/WOSSPA.2013.6602406

B. Koussa, S. Bachir, C. Perrine, C. Duvanaud, R. Vauzelle

引用次数: 2

Premature ventricular contraction arrhythmia detection using wavelet coefficients 利用小波系数检测室性早搏心律失常

2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA) Pub Date : 2013-05-12 DOI: 10.1109/WOSSPA.2013.6602356

M. Adnane, A. Belouchrani

引用次数: 9

Design of a multiblock general regression neural network for wind speed prediction in Algeria 阿尔及利亚风速预测的多块广义回归神经网络设计

2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA) Pub Date : 2013-05-12 DOI: 10.1109/WOSSPA.2013.6602397

F. Douak, N. Benoudjit, F. Melgani

引用次数: 3

Bayesian inference with hierarchical prior models for inverse problems in imaging systems 成像系统反问题的层次先验贝叶斯推理

2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA) Pub Date : 2013-05-12 DOI: 10.1109/WOSSPA.2013.6602329

A. Mohammad-Djafari

{"title":"Bayesian inference with hierarchical prior models for inverse problems in imaging systems","authors":"A. Mohammad-Djafari","doi":"10.1109/WOSSPA.2013.6602329","DOIUrl":"https://doi.org/10.1109/WOSSPA.2013.6602329","url":null,"abstract":"Bayesian approach is nowadays commonly used for inverse problems. Simple prior laws (Gaussian, Generalized Gaussian, Gauss-Markov and more general Markovian priors) are common in modeling and in their use in Bayesian inference methods. But, we need still more appropriate prior models which can account for non station-narities in signals and for the presence of the contours and homogeneous regions in images. Recently, we proposed a family of hierarchical prior models, called Gauss-Markov-Potts, which seems to be more appropriate for many applications in Imaging systems such as X ray Computed Tomography (CT) or Microwave imaging in Non Destructive Testing (NDT). In this tutorial paper, first some backgrounds on the Bayesian inference and the tools for assignment of priors and doing efficiently the Bayesian computation is presented. Then, more specifically hiearachical models and particularly the Gauss-Markov-Potts family of prior models are presented. Finally, their real applications in image restoration, in different practical Computed Tomography (CT) or other imaging systems are presented.","PeriodicalId":417940,"journal":{"name":"2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121448397","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: 4

Time frequency signal analysis and processing toolbox update 6.2: An enhanced research platform with new advanced high-resolution TFDs 时频信号分析与处理工具箱更新6.2:一个具有新的先进高分辨率tfd的增强研究平台

2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA) Pub Date : 2013-05-12 DOI: 10.1109/WOSSPA.2013.6602405

B. Boashash, M. Ghafoor

{"title":"Time frequency signal analysis and processing toolbox update 6.2: An enhanced research platform with new advanced high-resolution TFDs","authors":"B. Boashash, M. Ghafoor","doi":"10.1109/WOSSPA.2013.6602405","DOIUrl":"https://doi.org/10.1109/WOSSPA.2013.6602405","url":null,"abstract":"This paper describes the advancements, updates and improvements made in the new Time Frequency Signal Analysis TFSAP toolbox as compared with the previous TFSA toolbox version. The updates and improvements done in TFSA toolbox are in-line with the latest research done in recent few years in the field of time-frequency based signal analysis. TFSA Toolbox has proved in the past to be an efficient and popular tool for analyzing non-stationary signals. The new TFSAP Toolbox is an updated Matlab toolbox that extends the functionality of previous TFSA toolboxes. It provides additional options for generating new time-frequency distributions, and synthesizing a signal from its time-frequency distribution. It also includes options for analyzing real-life signals such as biomedical, speech and radar signals. Several demo scripts are also included in the new version to demonstrate the main functionality of the toolbox and to coach new users to use TFSA toolbox for advanced signal processing applications dealing with non-stationarities. The new version is renamed TFSAP 6.2; it can be downloaded for free as a service to the community.","PeriodicalId":417940,"journal":{"name":"2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133573360","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: 5