Pub Date : 2007-10-01DOI: 10.1109/WISP.2007.4447599
R. Alcaraz, J. J. Rieta
Atrial fibrillation (AF) is a common supraventricular arrhythmia with episodes that, in the first stages of the disease, may terminate spontaneously. This fact is referred as paroxysmal atrial fibrillation. The analysis of its termination or maintenance could avoid unnecessary therapy and contribute to take the appropriate decisions on its management. The aim of this work is to study if an AF episode terminates spontaneously or not by analyzing the increase of atrial activity (AA) organization prior to AF termination. The organization varies as a consequence of the decrease in the number of reentries into the atrial tissue. The analysis was carried out noninvasively through the use of surface electrocardiogram (ECG) recordings. Sample entropy was selected as non-linear organization index. It was observed that noise and ventricular residues degrade AA organization estimation performance, therefore the use of selective filtering to get the main atrial wave (MAW) was necessary. Using the MAW organization analysis, that is the signal produced by the main reentry wandering the atrial tissue, 46 out of 50 of the terminating and non-terminating analyzed AF episodes were correctly classified (92%). The obtained outcomes allow to conclude that the dominant atrial frequency, and therefore, the main atrial reentry, contains the most relevant information about spontaneous AF termination.
{"title":"Non-linear Regularity Analysis of Cardiac Atrial Signals","authors":"R. Alcaraz, J. J. Rieta","doi":"10.1109/WISP.2007.4447599","DOIUrl":"https://doi.org/10.1109/WISP.2007.4447599","url":null,"abstract":"Atrial fibrillation (AF) is a common supraventricular arrhythmia with episodes that, in the first stages of the disease, may terminate spontaneously. This fact is referred as paroxysmal atrial fibrillation. The analysis of its termination or maintenance could avoid unnecessary therapy and contribute to take the appropriate decisions on its management. The aim of this work is to study if an AF episode terminates spontaneously or not by analyzing the increase of atrial activity (AA) organization prior to AF termination. The organization varies as a consequence of the decrease in the number of reentries into the atrial tissue. The analysis was carried out noninvasively through the use of surface electrocardiogram (ECG) recordings. Sample entropy was selected as non-linear organization index. It was observed that noise and ventricular residues degrade AA organization estimation performance, therefore the use of selective filtering to get the main atrial wave (MAW) was necessary. Using the MAW organization analysis, that is the signal produced by the main reentry wandering the atrial tissue, 46 out of 50 of the terminating and non-terminating analyzed AF episodes were correctly classified (92%). The obtained outcomes allow to conclude that the dominant atrial frequency, and therefore, the main atrial reentry, contains the most relevant information about spontaneous AF termination.","PeriodicalId":164902,"journal":{"name":"2007 IEEE International Symposium on Intelligent Signal Processing","volume":"259 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116491985","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 : 2007-10-01DOI: 10.1109/WISP.2007.4447500
R. Iglesias, A. El Saddik
Haptics is the discipline that deals with the study of the complex sense of touch as an interface between human beings and machines. Haptic technology has been proven applicable and practical in many fields, including scientific visualization, medical training, authentication and other areas such as education and arts. This research investigates the usage of haptics as a mechanism to extract users' behaviors and to build a biometric system for authentication. We captured human behavior while users were interacting with two haptic devices: the Desktop PHANToM device (single-point interaction) and the CyberForce system (hand exoskeleton device). Experimental results, based on a set of haptic-based applications, show that single-point interaction haptic devices are suitable for authentication purposes. On the other hand, multiple-point haptic devices --hand exoskeleton devices-still seem to be far from being used in a haptic-biometric system. When using hand exoskeleton devices, the extracted features are not a good source of rich information to characterize a biometric identifier system.
{"title":"Haptics for Recognizing and Quantifying Hand Movement Patterns for Authentication","authors":"R. Iglesias, A. El Saddik","doi":"10.1109/WISP.2007.4447500","DOIUrl":"https://doi.org/10.1109/WISP.2007.4447500","url":null,"abstract":"Haptics is the discipline that deals with the study of the complex sense of touch as an interface between human beings and machines. Haptic technology has been proven applicable and practical in many fields, including scientific visualization, medical training, authentication and other areas such as education and arts. This research investigates the usage of haptics as a mechanism to extract users' behaviors and to build a biometric system for authentication. We captured human behavior while users were interacting with two haptic devices: the Desktop PHANToM device (single-point interaction) and the CyberForce system (hand exoskeleton device). Experimental results, based on a set of haptic-based applications, show that single-point interaction haptic devices are suitable for authentication purposes. On the other hand, multiple-point haptic devices --hand exoskeleton devices-still seem to be far from being used in a haptic-biometric system. When using hand exoskeleton devices, the extracted features are not a good source of rich information to characterize a biometric identifier system.","PeriodicalId":164902,"journal":{"name":"2007 IEEE International Symposium on Intelligent Signal Processing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133891908","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 : 2007-10-01DOI: 10.1109/WISP.2007.4447496
R. Petrocelli, L. De Micco, D. Carrica, H. Larrondo
This paper presents a digital acquisition method for low frequency signals immersed in high frequency noise. The method reduces the aliasing with no use of hardware aliasing filters. Several one-dimensional chaotic maps with different Invariant Probability Density Function (IPDF) are used to generate the sampling times. Comparisons with previous results using random sampling are made for several Finite Impulse Response (FIR) filters.
{"title":"Acquisition of Low Frequency Signals Immersed in Noise by Chaotic Sampling and FIR filters","authors":"R. Petrocelli, L. De Micco, D. Carrica, H. Larrondo","doi":"10.1109/WISP.2007.4447496","DOIUrl":"https://doi.org/10.1109/WISP.2007.4447496","url":null,"abstract":"This paper presents a digital acquisition method for low frequency signals immersed in high frequency noise. The method reduces the aliasing with no use of hardware aliasing filters. Several one-dimensional chaotic maps with different Invariant Probability Density Function (IPDF) are used to generate the sampling times. Comparisons with previous results using random sampling are made for several Finite Impulse Response (FIR) filters.","PeriodicalId":164902,"journal":{"name":"2007 IEEE International Symposium on Intelligent Signal Processing","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133907780","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 : 2007-10-01DOI: 10.1109/WISP.2007.4447570
S. Cóbreces, F. Huerta, D. Pizarro, F. Rodrguez, E. Bueno
This work presents a recursive algorithm to estimate the grid equivalent impedance and generator from the current and voltage measurements performed in the common coupling point, PCC, of a power converter. The method is based in a recursive least squares algorithm performed over the complex space. The described method works on-line, has low computational overhead and does not require the injection of disturbances in the grid.
{"title":"Three-phase power system parametric identification based on complex-space recursive least squares","authors":"S. Cóbreces, F. Huerta, D. Pizarro, F. Rodrguez, E. Bueno","doi":"10.1109/WISP.2007.4447570","DOIUrl":"https://doi.org/10.1109/WISP.2007.4447570","url":null,"abstract":"This work presents a recursive algorithm to estimate the grid equivalent impedance and generator from the current and voltage measurements performed in the common coupling point, PCC, of a power converter. The method is based in a recursive least squares algorithm performed over the complex space. The described method works on-line, has low computational overhead and does not require the injection of disturbances in the grid.","PeriodicalId":164902,"journal":{"name":"2007 IEEE International Symposium on Intelligent Signal Processing","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114847552","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 : 2007-10-01DOI: 10.1109/WISP.2007.4447512
Dimitrios Alexios Karras
This paper suggests a novel image compression scheme, using the discrete wavelet transformation (DWT) and the k-means clustering technique, suitable for medical images, based on preservation of important second order correlation ("textural") features of either DWT coefficients or image pixel intensities. Moreover it suggests a novel reconstruction scheme based on Bayesian formalism. While rival image compression methodologies utilizing the DWT apply it to the whole original image uniformly, the herein presented novel approaches involve a more sophisticated scheme. That is, different compression ratios are applied to the wavelet coefficients belonging in the different regions of interest, in which either each wavelet domain band of the transformed image or the image itself is clustered, respectively, employing textural descriptors as criteria. These descriptors include cooccurrence matrices based measures. Regarding the first method, its reconstruction process involves using the inverse DWT on the remaining wavelet coefficients. Concerning the second method, its reconstruction process involves linear combination of the reconstructed regions of interest. Moreover, another more efficient variant of these reconstruction approaches is proposed, which reduces blocking effects and is based on Bayesian formalism. An experimental study is conducted to qualitatively assessing all approaches in comparison with the original DWT compression technique, when applied to a set of medical images acquired from endoscopic video sequences.
{"title":"Improved Video Compression Schemes of Medical Image Sequences based on the Discrete Wavelet Transformation of Principal Textural Regions and Intelligent Restoration Techniques","authors":"Dimitrios Alexios Karras","doi":"10.1109/WISP.2007.4447512","DOIUrl":"https://doi.org/10.1109/WISP.2007.4447512","url":null,"abstract":"This paper suggests a novel image compression scheme, using the discrete wavelet transformation (DWT) and the k-means clustering technique, suitable for medical images, based on preservation of important second order correlation (\"textural\") features of either DWT coefficients or image pixel intensities. Moreover it suggests a novel reconstruction scheme based on Bayesian formalism. While rival image compression methodologies utilizing the DWT apply it to the whole original image uniformly, the herein presented novel approaches involve a more sophisticated scheme. That is, different compression ratios are applied to the wavelet coefficients belonging in the different regions of interest, in which either each wavelet domain band of the transformed image or the image itself is clustered, respectively, employing textural descriptors as criteria. These descriptors include cooccurrence matrices based measures. Regarding the first method, its reconstruction process involves using the inverse DWT on the remaining wavelet coefficients. Concerning the second method, its reconstruction process involves linear combination of the reconstructed regions of interest. Moreover, another more efficient variant of these reconstruction approaches is proposed, which reduces blocking effects and is based on Bayesian formalism. An experimental study is conducted to qualitatively assessing all approaches in comparison with the original DWT compression technique, when applied to a set of medical images acquired from endoscopic video sequences.","PeriodicalId":164902,"journal":{"name":"2007 IEEE International Symposium on Intelligent Signal Processing","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116186223","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 : 2007-10-01DOI: 10.1109/WISP.2007.4447627
B. Heredia, M. Ocaa, L. Bergasa, Miguel Angel Sotelo, P. Revenga, R. Flores, R. Barea, E. López
This work presents a people location system based on WiFi(Wireless-Fidelity) signal measure. The current locations systems based on WiFi are mainly applied in the location of indoor robots using the measure of their communications interface and the measures of other additional sensors. The advantage of the system presented in this work is that it is not necessary to add additional hardware (HW) to the people whom is tried to locate, neither in the environment, because we use the WiFi communications infrastructure. A probabilistic method based on a Hidden Markov Model (HMM) is used to determine the location of the people in the environment. In addition, a study of the WiFi signal measure is made in indoors with the main objective to obtain the necessary conclusions for the design of the system. The proposed method has been tested in a real environment. The results and conclusions obtained in the work are presented.
{"title":"People Location System based on WiFi Signal Measure","authors":"B. Heredia, M. Ocaa, L. Bergasa, Miguel Angel Sotelo, P. Revenga, R. Flores, R. Barea, E. López","doi":"10.1109/WISP.2007.4447627","DOIUrl":"https://doi.org/10.1109/WISP.2007.4447627","url":null,"abstract":"This work presents a people location system based on WiFi(Wireless-Fidelity) signal measure. The current locations systems based on WiFi are mainly applied in the location of indoor robots using the measure of their communications interface and the measures of other additional sensors. The advantage of the system presented in this work is that it is not necessary to add additional hardware (HW) to the people whom is tried to locate, neither in the environment, because we use the WiFi communications infrastructure. A probabilistic method based on a Hidden Markov Model (HMM) is used to determine the location of the people in the environment. In addition, a study of the WiFi signal measure is made in indoors with the main objective to obtain the necessary conclusions for the design of the system. The proposed method has been tested in a real environment. The results and conclusions obtained in the work are presented.","PeriodicalId":164902,"journal":{"name":"2007 IEEE International Symposium on Intelligent Signal Processing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132110118","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 : 2007-10-01DOI: 10.1109/WISP.2007.4447602
J. Vilaça, J. Fonseca
Today, the footwear industry is facing many challenges. First, consumers demand for new products with better comfort and design; second, competition is becoming stronger in current global market. Due to these factors, flexibility and rapidity in developing new products are key factors for the medium and long-term survival and success of the footwear industry. This paper proposes a new software application based in simple image processing techniques for optimization of two important steps of the processes involved in footwear manufacturing: the shoe sole halogenation and lead roughing process. The application presented in this paper has a friendly interface where the sole contour points for shoe sole halogenation and lead roughing are automatically determined. The operator can easily change and set new points to improve details within the interest region where tools will be applied, when the halogenation or the roughing process is executed. Another feature of this application is the automatic transformation of the 2D coordinates of the dominant points to 3D real world coordinates. This feature simplifies further ongoing work - automatic code generation for different industrial robots to execute the halogenation and roughing processes.
{"title":"A New Software Application for Footwear Industry","authors":"J. Vilaça, J. Fonseca","doi":"10.1109/WISP.2007.4447602","DOIUrl":"https://doi.org/10.1109/WISP.2007.4447602","url":null,"abstract":"Today, the footwear industry is facing many challenges. First, consumers demand for new products with better comfort and design; second, competition is becoming stronger in current global market. Due to these factors, flexibility and rapidity in developing new products are key factors for the medium and long-term survival and success of the footwear industry. This paper proposes a new software application based in simple image processing techniques for optimization of two important steps of the processes involved in footwear manufacturing: the shoe sole halogenation and lead roughing process. The application presented in this paper has a friendly interface where the sole contour points for shoe sole halogenation and lead roughing are automatically determined. The operator can easily change and set new points to improve details within the interest region where tools will be applied, when the halogenation or the roughing process is executed. Another feature of this application is the automatic transformation of the 2D coordinates of the dominant points to 3D real world coordinates. This feature simplifies further ongoing work - automatic code generation for different industrial robots to execute the halogenation and roughing processes.","PeriodicalId":164902,"journal":{"name":"2007 IEEE International Symposium on Intelligent Signal Processing","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132252305","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 : 2007-10-01DOI: 10.1109/WISP.2007.4447603
L.F. Zorzano, J. Zorzano, A. Martinez, A. Zorzano, J. Vicuña
This paper provides a description of an educational software for the application of neural network control to one case of nonlinear and unmodeled dynamic system as electrical drive for induction machines. This software facilitates practical teaching and learning about indirect field orientation control (IFOC) of induction machines and about intelligent control of induction machines with Real Time Recurrent Neural Networks (RTRNN) for overcoming IFOC limitations. Virtual laboratory includes virtual instruments for assisting the students in several areas: use of different reference frames, the induction machine behavior, IFOC principle and limitations, nonlinear identification with RTRNN and intelligent control for induction machines electrical drives. The software integrates all the tools needed in one only package and eliminates time dedicated to write source code, helping students in useful task as system control design and analysis.
{"title":"Virtual Laboratory for Intelligent Vector Control of AC Machines","authors":"L.F. Zorzano, J. Zorzano, A. Martinez, A. Zorzano, J. Vicuña","doi":"10.1109/WISP.2007.4447603","DOIUrl":"https://doi.org/10.1109/WISP.2007.4447603","url":null,"abstract":"This paper provides a description of an educational software for the application of neural network control to one case of nonlinear and unmodeled dynamic system as electrical drive for induction machines. This software facilitates practical teaching and learning about indirect field orientation control (IFOC) of induction machines and about intelligent control of induction machines with Real Time Recurrent Neural Networks (RTRNN) for overcoming IFOC limitations. Virtual laboratory includes virtual instruments for assisting the students in several areas: use of different reference frames, the induction machine behavior, IFOC principle and limitations, nonlinear identification with RTRNN and intelligent control for induction machines electrical drives. The software integrates all the tools needed in one only package and eliminates time dedicated to write source code, helping students in useful task as system control design and analysis.","PeriodicalId":164902,"journal":{"name":"2007 IEEE International Symposium on Intelligent Signal Processing","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134188916","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 : 2007-10-01DOI: 10.1109/WISP.2007.4447564
R. Munguía, A. Grau
The ego-motion online estimation process from a video input is often called visual odometry. Typically optical flow and structure from motion (SFM) techniques have been used for visual odometry. Monocular simultaneous localization and mapping (SLAM) techniques implicitly estimate camera ego-motion while incrementally build a map of the environment. However in monocular SLAM, when the number of features in the system state increases, the computational cost grows rapidly; consequently maintaining frame rate operation becomes impractical. In this paper monocular SLAM is proposed for map-based visual odometry. The number of features is bounded removing features dynamically from the system state, for maintaining a stable processing time. In the other hand if features are removed then previous visited sites can not be recognized, nevertheless in an odometry context this could not be a problem. A method for feature initialization and a simple method for recovery metric scale are proposed. The experimental results using real image sequences show that the scheme presented in this paper is promising.
{"title":"Monocular SLAM for Visual Odometry","authors":"R. Munguía, A. Grau","doi":"10.1109/WISP.2007.4447564","DOIUrl":"https://doi.org/10.1109/WISP.2007.4447564","url":null,"abstract":"The ego-motion online estimation process from a video input is often called visual odometry. Typically optical flow and structure from motion (SFM) techniques have been used for visual odometry. Monocular simultaneous localization and mapping (SLAM) techniques implicitly estimate camera ego-motion while incrementally build a map of the environment. However in monocular SLAM, when the number of features in the system state increases, the computational cost grows rapidly; consequently maintaining frame rate operation becomes impractical. In this paper monocular SLAM is proposed for map-based visual odometry. The number of features is bounded removing features dynamically from the system state, for maintaining a stable processing time. In the other hand if features are removed then previous visited sites can not be recognized, nevertheless in an odometry context this could not be a problem. A method for feature initialization and a simple method for recovery metric scale are proposed. The experimental results using real image sequences show that the scheme presented in this paper is promising.","PeriodicalId":164902,"journal":{"name":"2007 IEEE International Symposium on Intelligent Signal Processing","volume":"254 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134470682","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 : 2007-10-01DOI: 10.1109/WISP.2007.4447588
R. Precup, Z. Preitl, E. Petriu
The paper presents a new design method for low-cost fuzzy control systems used in mechatronics, characterized by second-order dynamics of integral type, controlled by two-degree-of-freedom Pi-fuzzy controllers. The method, referred to as delta domain design, consists of three design steps based on continuous-time linear case design results expressed in terms of the Extended Symmetrical Optimum method applied in the delta domain, followed by the transfer of these results to the fuzzy case. The new design method and Mamdani Pi-fuzzy controllers are validated by real-time experiments in controlling a nonlinear servosystem.
{"title":"Delta Domain Design of Low-Cost Fuzzy Controlled Servosystems","authors":"R. Precup, Z. Preitl, E. Petriu","doi":"10.1109/WISP.2007.4447588","DOIUrl":"https://doi.org/10.1109/WISP.2007.4447588","url":null,"abstract":"The paper presents a new design method for low-cost fuzzy control systems used in mechatronics, characterized by second-order dynamics of integral type, controlled by two-degree-of-freedom Pi-fuzzy controllers. The method, referred to as delta domain design, consists of three design steps based on continuous-time linear case design results expressed in terms of the Extended Symmetrical Optimum method applied in the delta domain, followed by the transfer of these results to the fuzzy case. The new design method and Mamdani Pi-fuzzy controllers are validated by real-time experiments in controlling a nonlinear servosystem.","PeriodicalId":164902,"journal":{"name":"2007 IEEE International Symposium on Intelligent Signal Processing","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133649602","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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