Pub Date : 2007-11-01DOI: 10.1109/ICSPC.2007.4728581
N. Nejatian, M. Nayebi, Ali A. Tadaion
In the sleep mode, a mobile subscribe station (MSS) sleeps for a sleep interval and wakes up at the end of this interval in order to check buffered packet(s) at base station (BS) destined to it. If there is no packet, the MSS increases the sleep window up to the maximum value or keeps it unchanged and sleeps again. In this paper, we study the effect of presence of multi service connections with different power saving classes (PSCs) on power consumption for IEEE 802.16e nodes while operating in the sleep mode. Using multi service connections may result in overlapping of availability and unavailability intervals and reducing the effectiveness of power saving mode of the subscriber.
{"title":"Power Consumption Evaluation of Sleep Mode in the IEEE 802.16e MAC with Multi Service Connections","authors":"N. Nejatian, M. Nayebi, Ali A. Tadaion","doi":"10.1109/ICSPC.2007.4728581","DOIUrl":"https://doi.org/10.1109/ICSPC.2007.4728581","url":null,"abstract":"In the sleep mode, a mobile subscribe station (MSS) sleeps for a sleep interval and wakes up at the end of this interval in order to check buffered packet(s) at base station (BS) destined to it. If there is no packet, the MSS increases the sleep window up to the maximum value or keeps it unchanged and sleeps again. In this paper, we study the effect of presence of multi service connections with different power saving classes (PSCs) on power consumption for IEEE 802.16e nodes while operating in the sleep mode. Using multi service connections may result in overlapping of availability and unavailability intervals and reducing the effectiveness of power saving mode of the subscriber.","PeriodicalId":425397,"journal":{"name":"2007 IEEE International Conference on Signal Processing and Communications","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115547020","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}
Pub Date : 2007-11-01DOI: 10.1109/ICSPC.2007.4728444
P. Ramos, F. Janeiro
In this paper, two DSP based algorithms are implemented for impedance measurements. The algorithms (the seven parameter sine-fitting algorithm and the ellipse fitting algorithm) are implemented and tested in a commercial DSP kit. The complete system is used to compare the algorithms by measuring 105 different impedances, using the four-wire impedance measurement method. The strategic selection of appropriate reference impedances, intrinsic to the impedance measurement method, is also described. The results of each algorithm are compared in terms of speed and accuracy. This is the ground work for a portable DSP based impedance measurement device to be implemented in specifically designed hardware.
{"title":"Implementation of DSP based Algorithms for Impedance Measurements","authors":"P. Ramos, F. Janeiro","doi":"10.1109/ICSPC.2007.4728444","DOIUrl":"https://doi.org/10.1109/ICSPC.2007.4728444","url":null,"abstract":"In this paper, two DSP based algorithms are implemented for impedance measurements. The algorithms (the seven parameter sine-fitting algorithm and the ellipse fitting algorithm) are implemented and tested in a commercial DSP kit. The complete system is used to compare the algorithms by measuring 105 different impedances, using the four-wire impedance measurement method. The strategic selection of appropriate reference impedances, intrinsic to the impedance measurement method, is also described. The results of each algorithm are compared in terms of speed and accuracy. This is the ground work for a portable DSP based impedance measurement device to be implemented in specifically designed hardware.","PeriodicalId":425397,"journal":{"name":"2007 IEEE International Conference on Signal Processing and Communications","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124496899","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}
Pub Date : 2007-11-01DOI: 10.1109/ICSPC.2007.4728281
Virginie Galtier, O. Pietquin
Feature selection is a key issue in many machine learning applications and the need to test lots of candidate features is real while computational time required to do so is often huge. In this paper, we introduce a parallel version of the well-known AdaBoost algorithm to speed up and size up feature selection for binary classification tasks using large training datasets and a wide range of elementary features. This parallelization is done without any modification to the AdaBoost algorithm and designed for PC clusters using Java and the JavaSpace distributed framework. JavaSpace is a memory sharing paradigm implemented on top of a virtual shared memory, that appears both efficient and easy-to-use. Results and performances on a face detection system trained with the proposed parallel AdaBoost are presented.
{"title":"AdaBoost Parallelization on PC Clusters with Virtual Shared Memory for Fast Feature Selection","authors":"Virginie Galtier, O. Pietquin","doi":"10.1109/ICSPC.2007.4728281","DOIUrl":"https://doi.org/10.1109/ICSPC.2007.4728281","url":null,"abstract":"Feature selection is a key issue in many machine learning applications and the need to test lots of candidate features is real while computational time required to do so is often huge. In this paper, we introduce a parallel version of the well-known AdaBoost algorithm to speed up and size up feature selection for binary classification tasks using large training datasets and a wide range of elementary features. This parallelization is done without any modification to the AdaBoost algorithm and designed for PC clusters using Java and the JavaSpace distributed framework. JavaSpace is a memory sharing paradigm implemented on top of a virtual shared memory, that appears both efficient and easy-to-use. Results and performances on a face detection system trained with the proposed parallel AdaBoost are presented.","PeriodicalId":425397,"journal":{"name":"2007 IEEE International Conference on Signal Processing and Communications","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114876240","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}
Pub Date : 2007-11-01DOI: 10.1109/ICSPC.2007.4728307
M. Alnaimi, S. Subramaniam
In this paper, we consider a unidirectional ring network with limited reconfigurability and take up the problem of supporting all-to-all traffic - while minimizing the worst-case wavelength range of the reconfigurable optical add drop multiplexers (ROADMs). ROADMs can be limited in range (L-ROADMs) or have full range (F-ROADMs). The cost of such a network is dominated by the number of wavelengths to be added or dropped by ROADMs. Limiting the range of wavelengths that can be accessed at a node reduces costs. Here, we develop an integer linear programming (ILP) formulation for this problem, and also propose a new wavelength assignment heuristic where we evalute it using the ILP formulation. We conclude that the performance of our proposed heuristic is very close to optimal and the worst-case range is only about 65% of the full range for moderately large number of network nodes.
{"title":"On Minimizing Band Size in Limited Reconfigurable Optical Networks","authors":"M. Alnaimi, S. Subramaniam","doi":"10.1109/ICSPC.2007.4728307","DOIUrl":"https://doi.org/10.1109/ICSPC.2007.4728307","url":null,"abstract":"In this paper, we consider a unidirectional ring network with limited reconfigurability and take up the problem of supporting all-to-all traffic - while minimizing the worst-case wavelength range of the reconfigurable optical add drop multiplexers (ROADMs). ROADMs can be limited in range (L-ROADMs) or have full range (F-ROADMs). The cost of such a network is dominated by the number of wavelengths to be added or dropped by ROADMs. Limiting the range of wavelengths that can be accessed at a node reduces costs. Here, we develop an integer linear programming (ILP) formulation for this problem, and also propose a new wavelength assignment heuristic where we evalute it using the ILP formulation. We conclude that the performance of our proposed heuristic is very close to optimal and the worst-case range is only about 65% of the full range for moderately large number of network nodes.","PeriodicalId":425397,"journal":{"name":"2007 IEEE International Conference on Signal Processing and Communications","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116896301","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}
Pub Date : 2007-11-01DOI: 10.1109/ICSPC.2007.4728457
M. Torabi, H. Moradzadeh, R. Vaziri, S. Razavian, R. Ardekani, M. Rahmandoust, A. Taalimi, E. Fatemizadeh
The paper presents an effective algorithm to analyze MR-images in order to recognize Alzheimer's disease (AD) which appeared in patient's brain. The features of interest are categorized in features of the spatial domain (FSD's) and Features of the frequency domain (FFD's) which are based on the first four statistic moments of the wavelet transform. Extracted features have been classified by a multi-layer perceptron artificial neural network (ANN). Before ANN, the number of features is reduced from 44 to 12 to optimize and eliminate any correlation between them. The contribution of this paper is to demonstrate that by using the wavelet transform number of features needed for AD diagnosis has been reduced in comparison with the previous work. We achieved 79% and 100% accuracy among test set and training set respectively, including 93 MR-images.
{"title":"Development of Alzheimer's Disease Recognition using Semiautomatic Analysis of Statistical Parameters based on Frequency Characteristics of Medical Images","authors":"M. Torabi, H. Moradzadeh, R. Vaziri, S. Razavian, R. Ardekani, M. Rahmandoust, A. Taalimi, E. Fatemizadeh","doi":"10.1109/ICSPC.2007.4728457","DOIUrl":"https://doi.org/10.1109/ICSPC.2007.4728457","url":null,"abstract":"The paper presents an effective algorithm to analyze MR-images in order to recognize Alzheimer's disease (AD) which appeared in patient's brain. The features of interest are categorized in features of the spatial domain (FSD's) and Features of the frequency domain (FFD's) which are based on the first four statistic moments of the wavelet transform. Extracted features have been classified by a multi-layer perceptron artificial neural network (ANN). Before ANN, the number of features is reduced from 44 to 12 to optimize and eliminate any correlation between them. The contribution of this paper is to demonstrate that by using the wavelet transform number of features needed for AD diagnosis has been reduced in comparison with the previous work. We achieved 79% and 100% accuracy among test set and training set respectively, including 93 MR-images.","PeriodicalId":425397,"journal":{"name":"2007 IEEE International Conference on Signal Processing and Communications","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117103704","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}
Pub Date : 2007-11-01DOI: 10.1109/ICSPC.2007.4728333
Woon-Yong Park, Y. Hong, Sungsoo Choi, Won-Cheol Lee
This paper proposes a scheme for time of arrival (TOA) estimation with employing low-bit analog-to-digital converters (ADCs). The proposed TOA estimation functions in two steps designated by coarse and fine processes to improve TOA accuracy. Towards this, dual overlapped window banks designated as primary and auxiliary windows are utilized together with the search back window (SBW). The performance of the proposed scheme is verified by conducting computer simulations presumed that two types of channel conditions are encountered. The simulation results show that the proposed TOA estimation scheme is superior rather than the conventional method specified by IEEE 802.15.4a technical document even in a condensed multipath environment.
{"title":"An Enhanced TOA Estimation using Search Back Window for Non-Coherent UWB Systems","authors":"Woon-Yong Park, Y. Hong, Sungsoo Choi, Won-Cheol Lee","doi":"10.1109/ICSPC.2007.4728333","DOIUrl":"https://doi.org/10.1109/ICSPC.2007.4728333","url":null,"abstract":"This paper proposes a scheme for time of arrival (TOA) estimation with employing low-bit analog-to-digital converters (ADCs). The proposed TOA estimation functions in two steps designated by coarse and fine processes to improve TOA accuracy. Towards this, dual overlapped window banks designated as primary and auxiliary windows are utilized together with the search back window (SBW). The performance of the proposed scheme is verified by conducting computer simulations presumed that two types of channel conditions are encountered. The simulation results show that the proposed TOA estimation scheme is superior rather than the conventional method specified by IEEE 802.15.4a technical document even in a condensed multipath environment.","PeriodicalId":425397,"journal":{"name":"2007 IEEE International Conference on Signal Processing and Communications","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117252248","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}
Pub Date : 2007-11-01DOI: 10.1109/ICSPC.2007.4728290
M. Salamah, E. Doukhnitch, C. Bayramer
There is an increasing demand for finding a mobile location in areas such as robotics applications, electronic warfare positioning, wireless communication systems and vehicle security. Angle of arrival (AOA) is one of the key techniques in wireless location estimation. Location estimation is done by using standard triangulation operations that are usually implemented in software. In this paper, we present a new hardware-oriented algorithm that uses only simple shift and add operations in the computation and therefore can be easily implemented in hardware. The comparison between this method and the conventional AOA based positioning technique is discussed in terms of computational cost (required number of operations). The results show that the proposed algorithm outperforms the traditional one in terms of both software and hardware implementations points of views.
{"title":"Dynamic Hardware-Oriented Algorithm for Angle of Arrival Positioning Technique","authors":"M. Salamah, E. Doukhnitch, C. Bayramer","doi":"10.1109/ICSPC.2007.4728290","DOIUrl":"https://doi.org/10.1109/ICSPC.2007.4728290","url":null,"abstract":"There is an increasing demand for finding a mobile location in areas such as robotics applications, electronic warfare positioning, wireless communication systems and vehicle security. Angle of arrival (AOA) is one of the key techniques in wireless location estimation. Location estimation is done by using standard triangulation operations that are usually implemented in software. In this paper, we present a new hardware-oriented algorithm that uses only simple shift and add operations in the computation and therefore can be easily implemented in hardware. The comparison between this method and the conventional AOA based positioning technique is discussed in terms of computational cost (required number of operations). The results show that the proposed algorithm outperforms the traditional one in terms of both software and hardware implementations points of views.","PeriodicalId":425397,"journal":{"name":"2007 IEEE International Conference on Signal Processing and Communications","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120864783","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}
Pub Date : 2007-11-01DOI: 10.1109/ICSPC.2007.4728552
W. Hernandez
In this paper, a recursive least-squares lattice (RLSL) adaptive filter was used to estimate the relevant signal coming from an ADXL202 accelerometer placed in car under performance tests. In this practical application, the signal of interest was buried in a broad-band noise background where we had little knowledge of the noise characteristics. The results of the experiment were satisfactory and, in order to compare the type of conventional filters used in today's cars to cancel the noise corrupting the information coming from automotive sensors against optimal adaptive filters, the signal coming from the ADXL202 was also filtered by using several lowpass digital Butterworth filters. The results of the experiment showed that the signal-to-noise (SNR) ratio improvement achieved by using the RLSL adaptive filter was 42.66 times better than the best SNR improvement that was achieved by using the classical filters.
{"title":"Improving the Real-Time Response of an ADXL202 Accelerometer Placed in a Car Under Performance Tests by using Adaptive Filtering","authors":"W. Hernandez","doi":"10.1109/ICSPC.2007.4728552","DOIUrl":"https://doi.org/10.1109/ICSPC.2007.4728552","url":null,"abstract":"In this paper, a recursive least-squares lattice (RLSL) adaptive filter was used to estimate the relevant signal coming from an ADXL202 accelerometer placed in car under performance tests. In this practical application, the signal of interest was buried in a broad-band noise background where we had little knowledge of the noise characteristics. The results of the experiment were satisfactory and, in order to compare the type of conventional filters used in today's cars to cancel the noise corrupting the information coming from automotive sensors against optimal adaptive filters, the signal coming from the ADXL202 was also filtered by using several lowpass digital Butterworth filters. The results of the experiment showed that the signal-to-noise (SNR) ratio improvement achieved by using the RLSL adaptive filter was 42.66 times better than the best SNR improvement that was achieved by using the classical filters.","PeriodicalId":425397,"journal":{"name":"2007 IEEE International Conference on Signal Processing and Communications","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125874396","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}
Pub Date : 2007-11-01DOI: 10.1109/ICSPC.2007.4728304
Wang Yiding, Wang Yunhong, Z. Shi
Two kinds of spectrum inversion methods are investigated. One is analog mixing method; another is digital undersampling method, which is put forward in this paper. In order to prove the digital undersampling method is better than the analog mixing method. The error models of these two methods are set up. Based on the error models, simulation experiments are carried out. The results prove that the digital undersampling method is of much more precision than the analog mixing method.
{"title":"Errors Analysis of Spectrum Inversion Methods","authors":"Wang Yiding, Wang Yunhong, Z. Shi","doi":"10.1109/ICSPC.2007.4728304","DOIUrl":"https://doi.org/10.1109/ICSPC.2007.4728304","url":null,"abstract":"Two kinds of spectrum inversion methods are investigated. One is analog mixing method; another is digital undersampling method, which is put forward in this paper. In order to prove the digital undersampling method is better than the analog mixing method. The error models of these two methods are set up. Based on the error models, simulation experiments are carried out. The results prove that the digital undersampling method is of much more precision than the analog mixing method.","PeriodicalId":425397,"journal":{"name":"2007 IEEE International Conference on Signal Processing and Communications","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126100415","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}
Pub Date : 2007-11-01DOI: 10.1109/ICSPC.2007.4728295
F. Beritelli, S. Casale, A. Russo, S. Serrano
The paper presents an adaptive system for voiced/unvoiced (V/UV) speech detection in the presence of background noise. Genetic algorithms were used to select the features that offer the best V/UV detection according to the output of a background noise classifier (NC) and a signal to noise ratio estimation (SNRE) system. The system was implemented and the tests performed using the TIMIT speech corpus and its phonetic classification. The results were compared with a non-adaptive classification system and the V/UV detectors adopted by three important speech coding standards: LPC10, ITU-T G.723.1 and ETSI AMR. In all cases the adaptive V/UV classifier outperformed the traditional solutions.
{"title":"A V/UV Speech Detection based on Characterization of Background Noise","authors":"F. Beritelli, S. Casale, A. Russo, S. Serrano","doi":"10.1109/ICSPC.2007.4728295","DOIUrl":"https://doi.org/10.1109/ICSPC.2007.4728295","url":null,"abstract":"The paper presents an adaptive system for voiced/unvoiced (V/UV) speech detection in the presence of background noise. Genetic algorithms were used to select the features that offer the best V/UV detection according to the output of a background noise classifier (NC) and a signal to noise ratio estimation (SNRE) system. The system was implemented and the tests performed using the TIMIT speech corpus and its phonetic classification. The results were compared with a non-adaptive classification system and the V/UV detectors adopted by three important speech coding standards: LPC10, ITU-T G.723.1 and ETSI AMR. In all cases the adaptive V/UV classifier outperformed the traditional solutions.","PeriodicalId":425397,"journal":{"name":"2007 IEEE International Conference on Signal Processing and Communications","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129782559","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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