Pub Date : 2012-09-05DOI: 10.1109/IRANIANCEE.2012.6292444
F. Fooladgar, S. Samavi, S. Soroushmehr
Determining location of a target in a specific region is an important goal in some machine vision applications. The accuracy of the target localization is related to a number of parameters. Quantization process in the CCD of a camera node is one of the sources of error which results in achieving an estimation of the target location instead of its exact position. In this paper, we present a geometrical approach to analyze this error. The proposed approach models the field of view of each pixel as an oblique cone. Thus the ambiguity in localization, via two cameras with arbitrary configurations, is considered by intersection of two oblique cones. In this paper we utilize the difference between the maximum and minimum points of the cones intersection, in all three dimensions, as a criterion of error estimation. In order to determine the extremum points, the Lagrangain method is used. We show the validity of our model through simulations. Also, we analyze the effect of varying many parameters such as the baseline length, focal length, and pixel size, on the amount of the estimation error.
{"title":"Geometrical analysis of altitude estimation error caused by pixel quantization in stereo vision","authors":"F. Fooladgar, S. Samavi, S. Soroushmehr","doi":"10.1109/IRANIANCEE.2012.6292444","DOIUrl":"https://doi.org/10.1109/IRANIANCEE.2012.6292444","url":null,"abstract":"Determining location of a target in a specific region is an important goal in some machine vision applications. The accuracy of the target localization is related to a number of parameters. Quantization process in the CCD of a camera node is one of the sources of error which results in achieving an estimation of the target location instead of its exact position. In this paper, we present a geometrical approach to analyze this error. The proposed approach models the field of view of each pixel as an oblique cone. Thus the ambiguity in localization, via two cameras with arbitrary configurations, is considered by intersection of two oblique cones. In this paper we utilize the difference between the maximum and minimum points of the cones intersection, in all three dimensions, as a criterion of error estimation. In order to determine the extremum points, the Lagrangain method is used. We show the validity of our model through simulations. Also, we analyze the effect of varying many parameters such as the baseline length, focal length, and pixel size, on the amount of the estimation error.","PeriodicalId":308726,"journal":{"name":"20th Iranian Conference on Electrical Engineering (ICEE2012)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127164713","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 : 2012-09-05DOI: 10.1109/IRANIANCEE.2012.6292393
M. Nabipour, H. Abootorabi Zarchi, S. M. Madani
A family of variable structure robust position tracking controller is presented for a three-phase synchronous reluctance motor (SynRM) considering the maximum torque control (MTC) strategy related to this motor. Neglecting the iron losses, the proposed controller is designed including one of the three classes of linear variable structure controller and adaptive input-output feedback linearization (AIOFL) approaches. Foremost, a sliding mode-plus-PI controller is used to obtain the stator current reference signal. For that stage, three classes of a PI-sliding controller are presented. These methods are then compared and its characteristics are specified and the optimum use for any case, determined. The presented position controller is fast response and robust against mechanical parameter uncertainties and load torque disturbance. At Second stage, the proposed sliding mode based AIOFL controller estimates the unknown electrical uncertainties without using sign(.) or sat(.) function. Hence, it reduces chattering or steady state error phenomenon. Finally, the effectiveness and feasibility of the proposed control approach is demonstrated by computer simulation. The results obtained confirm that the desired position reference command is perfectly tracked in spite of motor parameter uncertainties and load torque disturbance.
{"title":"Variable-structure position control-a class of fast and robust controllers for synchronous reluctance motor drives","authors":"M. Nabipour, H. Abootorabi Zarchi, S. M. Madani","doi":"10.1109/IRANIANCEE.2012.6292393","DOIUrl":"https://doi.org/10.1109/IRANIANCEE.2012.6292393","url":null,"abstract":"A family of variable structure robust position tracking controller is presented for a three-phase synchronous reluctance motor (SynRM) considering the maximum torque control (MTC) strategy related to this motor. Neglecting the iron losses, the proposed controller is designed including one of the three classes of linear variable structure controller and adaptive input-output feedback linearization (AIOFL) approaches. Foremost, a sliding mode-plus-PI controller is used to obtain the stator current reference signal. For that stage, three classes of a PI-sliding controller are presented. These methods are then compared and its characteristics are specified and the optimum use for any case, determined. The presented position controller is fast response and robust against mechanical parameter uncertainties and load torque disturbance. At Second stage, the proposed sliding mode based AIOFL controller estimates the unknown electrical uncertainties without using sign(.) or sat(.) function. Hence, it reduces chattering or steady state error phenomenon. Finally, the effectiveness and feasibility of the proposed control approach is demonstrated by computer simulation. The results obtained confirm that the desired position reference command is perfectly tracked in spite of motor parameter uncertainties and load torque disturbance.","PeriodicalId":308726,"journal":{"name":"20th Iranian Conference on Electrical Engineering (ICEE2012)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132913207","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 : 2012-09-05DOI: 10.1109/IRANIANCEE.2012.6292519
Z. Firouzeh, M. Ghaffari‐Miab, R. Faraji-Dana, R. Moini, S. Sadeghi, G. Vandenbosch
The transient scattering of a thin wire buried in a half-space is calculated by a novel Time-Domain Mixed Potential Integral Equation (TD-MPIE), using complex-time Green's functions. The TD-MPIE is solved by MoM in time domain along with a Marching-On-in-Time (MOT) procedure. The excitation is a Gaussian plane wave and Band-Limited Second-Order Lagrange (BL-2L) functions are used as Temporal Basis Functions (TBFs). Numerical results show that the solution using BL-2L TBFs is stable and accurate, without late-time instabilities, and efficient in computation.
{"title":"Time-domain MoM for the scattering analysis of thin-wire structures within a ground using band-limited Second-Order Lagrange temporal basis functions","authors":"Z. Firouzeh, M. Ghaffari‐Miab, R. Faraji-Dana, R. Moini, S. Sadeghi, G. Vandenbosch","doi":"10.1109/IRANIANCEE.2012.6292519","DOIUrl":"https://doi.org/10.1109/IRANIANCEE.2012.6292519","url":null,"abstract":"The transient scattering of a thin wire buried in a half-space is calculated by a novel Time-Domain Mixed Potential Integral Equation (TD-MPIE), using complex-time Green's functions. The TD-MPIE is solved by MoM in time domain along with a Marching-On-in-Time (MOT) procedure. The excitation is a Gaussian plane wave and Band-Limited Second-Order Lagrange (BL-2L) functions are used as Temporal Basis Functions (TBFs). Numerical results show that the solution using BL-2L TBFs is stable and accurate, without late-time instabilities, and efficient in computation.","PeriodicalId":308726,"journal":{"name":"20th Iranian Conference on Electrical Engineering (ICEE2012)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127299844","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 : 2012-05-18DOI: 10.1109/EEEIC.2012.6221581
S. Astinfeshan, A. Gholami, M. Mohajeri
This paper presents a model of lightning performance of a 400kV double circuit overhead transmission line using ATP/EMTP. Including the models of transmission line, tower surge response, footing impedance, impulse electric strength of line insulator and lightning stroke as well as corona, the paper introduces a comprehensive lightning transients study. Based on this model, the paper discussed the influence of corona on two transient phenomena known as back flashover and shielding failure.
{"title":"Analysis of corona effect on lightning performance of HV overhead transmission line using ATP/EMTP","authors":"S. Astinfeshan, A. Gholami, M. Mohajeri","doi":"10.1109/EEEIC.2012.6221581","DOIUrl":"https://doi.org/10.1109/EEEIC.2012.6221581","url":null,"abstract":"This paper presents a model of lightning performance of a 400kV double circuit overhead transmission line using ATP/EMTP. Including the models of transmission line, tower surge response, footing impedance, impulse electric strength of line insulator and lightning stroke as well as corona, the paper introduces a comprehensive lightning transients study. Based on this model, the paper discussed the influence of corona on two transient phenomena known as back flashover and shielding failure.","PeriodicalId":308726,"journal":{"name":"20th Iranian Conference on Electrical Engineering (ICEE2012)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128865811","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 : 2012-05-15DOI: 10.1109/IRANIANCEE.2012.6292427
A. Ghazikhani, R. Monsefi, H. Yazdi
We propose a novel algorithm for handling class imbalance in the k-NN classifier. Class imbalance is a problem occurring in some valuable data such as medical diagnosis, fraud detection, oil spills and etc. The problem influences all supervised classification algorithms therefore a large amount of research is being done. We tackle the problem by preprocessing the data using oversampling techniques. A two phase algorithm, based on Support Vector Data Description (SVDD) is proposed. SVDD is a tool for data description. In our approach we firstly describe data from the minority class i.e. the class with less data using SVDD. This is followed by oversampling of the support vectors, which is suitable for k-NN. We evaluate our method using real world datasets with different imbalance ratios and compare it with four other oversampling methods namely SMOTE, Borderline SMOTE, random oversampling and cluster based sampling. The results show that the proposed algorithm is a suitable preprocessing method for the k-NN classifier.
{"title":"SVBO: Support Vector-Based Oversampling for handling class imbalance in k-NN","authors":"A. Ghazikhani, R. Monsefi, H. Yazdi","doi":"10.1109/IRANIANCEE.2012.6292427","DOIUrl":"https://doi.org/10.1109/IRANIANCEE.2012.6292427","url":null,"abstract":"We propose a novel algorithm for handling class imbalance in the k-NN classifier. Class imbalance is a problem occurring in some valuable data such as medical diagnosis, fraud detection, oil spills and etc. The problem influences all supervised classification algorithms therefore a large amount of research is being done. We tackle the problem by preprocessing the data using oversampling techniques. A two phase algorithm, based on Support Vector Data Description (SVDD) is proposed. SVDD is a tool for data description. In our approach we firstly describe data from the minority class i.e. the class with less data using SVDD. This is followed by oversampling of the support vectors, which is suitable for k-NN. We evaluate our method using real world datasets with different imbalance ratios and compare it with four other oversampling methods namely SMOTE, Borderline SMOTE, random oversampling and cluster based sampling. The results show that the proposed algorithm is a suitable preprocessing method for the k-NN classifier.","PeriodicalId":308726,"journal":{"name":"20th Iranian Conference on Electrical Engineering (ICEE2012)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123141112","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 : 2012-05-15DOI: 10.1109/IRANIANCEE.2012.6292515
M. Kamnadar, H. Ghassemian
In this paper, we propose a new linear feature extraction scheme for hyperspectral images. A modified Maximum relevance, Min redundancy (MRMD) is used as a criterion for linear feature extraction. Parzen density estimator and instantaneous entropy estimation are used for estimating mutual information. Using Instantaneous entropy estimator mitigates nonstationary behavior of the hyperspectral data and reduces computational cost. Based on proposed estimator and MRMD, an algorithm for linear feature extraction in hyperspectral images is designed that is less offended by Hueghs phenomenon and has less computation cost for applying to hyperspectral images. An ascent gradient algorithm is used for optimizing proposed criterion with respect to parameters of a linear transform. Preliminary results achieve better classification comparing the traditional methods.
{"title":"Linear feature extraction for hyperspectral images using information theoretic learning","authors":"M. Kamnadar, H. Ghassemian","doi":"10.1109/IRANIANCEE.2012.6292515","DOIUrl":"https://doi.org/10.1109/IRANIANCEE.2012.6292515","url":null,"abstract":"In this paper, we propose a new linear feature extraction scheme for hyperspectral images. A modified Maximum relevance, Min redundancy (MRMD) is used as a criterion for linear feature extraction. Parzen density estimator and instantaneous entropy estimation are used for estimating mutual information. Using Instantaneous entropy estimator mitigates nonstationary behavior of the hyperspectral data and reduces computational cost. Based on proposed estimator and MRMD, an algorithm for linear feature extraction in hyperspectral images is designed that is less offended by Hueghs phenomenon and has less computation cost for applying to hyperspectral images. An ascent gradient algorithm is used for optimizing proposed criterion with respect to parameters of a linear transform. Preliminary results achieve better classification comparing the traditional methods.","PeriodicalId":308726,"journal":{"name":"20th Iranian Conference on Electrical Engineering (ICEE2012)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123092307","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 : 2012-05-15DOI: 10.1109/IRANIANCEE.2012.6292617
H. Ghaheri, A. Ahmadyfard
Brain Computer Interface (BCI) is a system which straightly converts the acquired brain signals such as Electroencephalogram (EEG) to commands for controlling external devices. One of the most successful methods in Motor Imagery based BCI applications is Common Spatial method (CSP). In existing methods based on CSP, the spatial filters are extracted from the whole EEG signal as one time segment. In this study we use the fact that ERD/ERS events are not steady over time. This means that the importance of EEG channels vary for different time segments. Therefore we divide EEG signals into a number of time segments. Then we extract a feature vector from each time segment using CSP. We use OVR (One-Versus-the Rest) algorithm to break four classes problem into two classes problems. The considered four classes MI are left hand, right hand, foot and tongue. We used dataset 2a of BCI competition IV to evaluate our method. The result of experiment shows that this method outperforms both CSP and the best competitor of the BCI competition IV. In fact the effect of noise and outliers on extracted features is reduced by the proposed time windowing method.
脑机接口(BCI)是将采集到的脑电图(EEG)等脑信号直接转换为控制外部设备的命令的系统。在基于运动图像的脑机接口应用中，最成功的方法之一是公共空间方法(CSP)。在现有的基于CSP的方法中，将整个脑电信号作为一个时间段提取空间滤波器。在这项研究中，我们使用了ERD/ERS事件不随时间稳定的事实。这意味着脑电通道的重要性在不同的时间段有所不同。因此，我们将脑电信号分成若干个时间段。然后利用CSP算法从每个时间段提取特征向量。我们使用OVR (one - vs -the Rest)算法将四类问题分解为两类问题。MI的四个类别是左手、右手、脚和舌头。我们使用BCI竞赛IV的数据集2a来评估我们的方法。实验结果表明，该方法优于CSP和BCI竞争IV的最佳竞争者。实际上，所提出的时间窗方法降低了噪声和异常值对提取特征的影响。
{"title":"Temporal windowing in CSP method for multi-class Motor Imagery Classification","authors":"H. Ghaheri, A. Ahmadyfard","doi":"10.1109/IRANIANCEE.2012.6292617","DOIUrl":"https://doi.org/10.1109/IRANIANCEE.2012.6292617","url":null,"abstract":"Brain Computer Interface (BCI) is a system which straightly converts the acquired brain signals such as Electroencephalogram (EEG) to commands for controlling external devices. One of the most successful methods in Motor Imagery based BCI applications is Common Spatial method (CSP). In existing methods based on CSP, the spatial filters are extracted from the whole EEG signal as one time segment. In this study we use the fact that ERD/ERS events are not steady over time. This means that the importance of EEG channels vary for different time segments. Therefore we divide EEG signals into a number of time segments. Then we extract a feature vector from each time segment using CSP. We use OVR (One-Versus-the Rest) algorithm to break four classes problem into two classes problems. The considered four classes MI are left hand, right hand, foot and tongue. We used dataset 2a of BCI competition IV to evaluate our method. The result of experiment shows that this method outperforms both CSP and the best competitor of the BCI competition IV. In fact the effect of noise and outliers on extracted features is reduced by the proposed time windowing method.","PeriodicalId":308726,"journal":{"name":"20th Iranian Conference on Electrical Engineering (ICEE2012)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115754843","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 : 2012-05-15DOI: 10.1109/IRANIANCEE.2012.6292362
M. Mottaghi-Kashtiban, A. Jalali
A new class of digital FIR filters with application to the decimation filter design for ΣΔ Analog to Digital Converters (ADCs) is introduced, which can be realized using an efficient multiplier-less structure. The filter coefficients are conditioned in such a way that, independent of the order, the realization structure comprises shifts (delays) and only two additions; hence the proposed filters have close relation to the first order Cascaded Integrator-Comb (CIC) filters, but offering more design parameters to overcome their limited degree of freedom. A filter Involving Shifts and Only Two Additions (abbreviated as ISOTA), has coefficients dependant to each other; this together with the non-linearity of the discrete-space of the coefficients, makes the design procedure somewhat limited. A simple design method is used to find the desired solutions, based on applying gradient search algorithm to the possible combinations of the coefficients (obtained by state tree diagram). Demonstrative examples as well as the practical application are presented.
{"title":"Efficient decimation filters for ΣΔ ADCs, using new FIR filters involving shift s and only two additions","authors":"M. Mottaghi-Kashtiban, A. Jalali","doi":"10.1109/IRANIANCEE.2012.6292362","DOIUrl":"https://doi.org/10.1109/IRANIANCEE.2012.6292362","url":null,"abstract":"A new class of digital FIR filters with application to the decimation filter design for ΣΔ Analog to Digital Converters (ADCs) is introduced, which can be realized using an efficient multiplier-less structure. The filter coefficients are conditioned in such a way that, independent of the order, the realization structure comprises shifts (delays) and only two additions; hence the proposed filters have close relation to the first order Cascaded Integrator-Comb (CIC) filters, but offering more design parameters to overcome their limited degree of freedom. A filter Involving Shifts and Only Two Additions (abbreviated as ISOTA), has coefficients dependant to each other; this together with the non-linearity of the discrete-space of the coefficients, makes the design procedure somewhat limited. A simple design method is used to find the desired solutions, based on applying gradient search algorithm to the possible combinations of the coefficients (obtained by state tree diagram). Demonstrative examples as well as the practical application are presented.","PeriodicalId":308726,"journal":{"name":"20th Iranian Conference on Electrical Engineering (ICEE2012)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127220184","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 : 2012-05-15DOI: 10.1109/IRANIANCEE.2012.6292512
M. Z. Chahooki, N. M. Charkari
Shape features are powerful clues for object recognition. In this paper, for improving retrieval accuracy, dissimilarities of contour and region-based shape retrieval methods were used. It is assumed that the fusion of two categories of shape feature spaces causes a considerable improvement in retrieval performance. Fusion of multiple feature spaces can be done in constructing shape description vector and in decision phase. The method proposed in this paper is based on kNN by fusion in calculating of dissimilarity between test and other train samples. Our proposed fused kNN versus fusion of multiple kNNs has better accuracy results in shape classification. The proposed approach has been tested on Chicken Piece dataset. In the experiments, our method demonstrates effective performance compared with other algorithms.
{"title":"Supervised shape retrieval based on fusion of multiple feature spaces","authors":"M. Z. Chahooki, N. M. Charkari","doi":"10.1109/IRANIANCEE.2012.6292512","DOIUrl":"https://doi.org/10.1109/IRANIANCEE.2012.6292512","url":null,"abstract":"Shape features are powerful clues for object recognition. In this paper, for improving retrieval accuracy, dissimilarities of contour and region-based shape retrieval methods were used. It is assumed that the fusion of two categories of shape feature spaces causes a considerable improvement in retrieval performance. Fusion of multiple feature spaces can be done in constructing shape description vector and in decision phase. The method proposed in this paper is based on kNN by fusion in calculating of dissimilarity between test and other train samples. Our proposed fused kNN versus fusion of multiple kNNs has better accuracy results in shape classification. The proposed approach has been tested on Chicken Piece dataset. In the experiments, our method demonstrates effective performance compared with other algorithms.","PeriodicalId":308726,"journal":{"name":"20th Iranian Conference on Electrical Engineering (ICEE2012)","volume":"98 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124853511","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 : 2012-05-15DOI: 10.1109/IRANIANCEE.2012.6292557
M. Johnny, J. Mirzaee
According to the U.S. Federal Standard coder for 2400 bps, a data frame containing 54 bits of encoded signals are transmitted every 22.5 (ms). In each frame, 25 bits encode the spectral features (10 Line Spectrum Frequencies (LSF)). This paper describes a method to reduce the transmission rate while preserving most of the quality and intelligibility. The performance of the proposed coder is at about 780 bits/sec ( = 6 bits/frame × 130 frames/sec). In transmitter, we apply an algorithm to convert speech in to phonetic segments, and then these segments are bifurcated in to the voiced and unvoiced segments. Because of the fact that the spelling time of unvoiced phonetics is short, one cannot distinguish who is pronouncing them, either a male or a female. Literatures in this context show that in most cases, the aforementioned observation is admitted. Therefore, for high accuracy speech transmission, voiced phonetics are more important than unvoiced ones. Hence, a Voiced/Unvoiced decomposition system is proposed. Furthermore, in order to cluster voice segments, fuzzy clustering is applied, in which the proper number of voice segments is determined by a means of statistical method called “Elbow”. Depending on the transmission rate, two different strategies can be utilized. In the first strategy, unvoiced segments of speech can be transmitted by the use of Linear Predictive Coding (LPC) for high quality (MOS=4.5). As a second, unvoiced segments of speech can be recognized and then transmitted for lower quality (MOS=3) and under 100 bits/sec.
{"title":"A fuzzy based very low bit rate speech coding with high accuracy","authors":"M. Johnny, J. Mirzaee","doi":"10.1109/IRANIANCEE.2012.6292557","DOIUrl":"https://doi.org/10.1109/IRANIANCEE.2012.6292557","url":null,"abstract":"According to the U.S. Federal Standard coder for 2400 bps, a data frame containing 54 bits of encoded signals are transmitted every 22.5 (ms). In each frame, 25 bits encode the spectral features (10 Line Spectrum Frequencies (LSF)). This paper describes a method to reduce the transmission rate while preserving most of the quality and intelligibility. The performance of the proposed coder is at about 780 bits/sec ( = 6 bits/frame × 130 frames/sec). In transmitter, we apply an algorithm to convert speech in to phonetic segments, and then these segments are bifurcated in to the voiced and unvoiced segments. Because of the fact that the spelling time of unvoiced phonetics is short, one cannot distinguish who is pronouncing them, either a male or a female. Literatures in this context show that in most cases, the aforementioned observation is admitted. Therefore, for high accuracy speech transmission, voiced phonetics are more important than unvoiced ones. Hence, a Voiced/Unvoiced decomposition system is proposed. Furthermore, in order to cluster voice segments, fuzzy clustering is applied, in which the proper number of voice segments is determined by a means of statistical method called “Elbow”. Depending on the transmission rate, two different strategies can be utilized. In the first strategy, unvoiced segments of speech can be transmitted by the use of Linear Predictive Coding (LPC) for high quality (MOS=4.5). As a second, unvoiced segments of speech can be recognized and then transmitted for lower quality (MOS=3) and under 100 bits/sec.","PeriodicalId":308726,"journal":{"name":"20th Iranian Conference on Electrical Engineering (ICEE2012)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125006275","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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