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2011 2nd IEEE International Conference on Signal and Image processing Applications, ICSIPA 2011

作者： Fathi-Azar, Elham Setarehdan, Seyed Kamaledin Control and Intelligent Processing Center of Excellence College of Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781457702419

This paper presents an automated algorithm for shadow regions detection in IVUS images using a histogram modification method for threshold selection. The method employs the Type2 Fuzzy Set together with spatial information for shadow region separation from the background image. Shadow regions usually occur behind the calcium deposits making it difficult or impossible to process tissue images in these regions. Results show that the proposed method is effective in detection of parts of the image in the shadow regions. Applying to a data set of 40 IVUS frames the results show a good agreement between the automatically detected and manually defined shadow regions boundaries by the proposed method and the expert, respectively. © 2011 IEEE.

关键词： Graphic methods

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R-R interval simulation based on power spectrum curve fitting

R-R interval simulation based on power spectrum curve fittin...

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2013 20th Iranian Conference on Biomedical Engineering, ICBME 2013

作者： Aram, Zainab Setarehdan, Seyed Kamaledin Control and Intelligent Processing Center of Excellence College of Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781479932320

Analysis of heart rate variability (HRV) is one of the most important noninvasive methods of measuring autonomic nervous system (ANS) activities. Hence, simulation of a realistic sequence of HRV signal can have a significant impact on diagnosis of different diseases related to ANS. In this paper, the focus is on generating realistic R-R interval signals using frequency domain analysis. An algorithm was developed using power spectrum curve fitting. The proposed method was compared to two previously reported algorithms. Twenty different sequences of data were generated with each of the three techniques. The performances of the three methods were then evaluated by exerting a frequency domain classification method to the generated data of each technique and the results were compared to each other. © 2013 IEEE.

关键词： Curve fitting

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Kinematics modeling of a wheel-based Pole Climbing Robot (UT-PCR)

Kinematics modeling of a wheel-based Pole Climbing Robot (UT...

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2005 IEEE International Conference on Robotics and Automation

作者： Baghani, Ali Nili Ahmadabadi, Majid Harati, Ahad Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran

ISBN: (纸本)078038914X

This paper is concerned with the derivation of the kinematics model of the University of Tehran-Pole Climbing Robot (UT-PCR). As the first step, an appropriate set of coordinates is selected and used to describe the state of the robot. Nonholonomic constraints imposed by the wheels are then expressed as a set of differential equations. By describing these equations in terms of the state of the robot an underactuated driftless nonlinear control system with affine inputs that governs the motion of the robot is derived. A set of experimental results are also given to show the capability of the UT-PCR in climbing a stepped pole. ©2005 IEEE.

关键词： Mobile robots

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Adaptive Locally Linear Embedding

arXiv

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arXiv 2025年

作者： Goli, Ali Alizadeh, Mahdieh Yazdi, Hadi Sadoghi Department of Computer Engineering Ferdowsi University of Mashhad Mashhad Iran Center of Excellence in Soft Computing and Intelligent Information Processing Ferdowsi University of Mashhad Mashhad Iran

Manifold learning techniques, such as Locally linear embedding (LLE), are designed to preserve the local neighborhood structures of high-dimensional data during dimensionality reduction. Traditional LLE employs Euclidean distance to define neighborhoods, which can struggle to capture the intrinsic geometric relationships within complex data. A novel approach, Adaptive locally linear embedding(ALLE), is introduced to address this limitation by incorporating a dynamic, data-driven metric that enhances topological preservation. This method redefines the concept of proximity by focusing on topological neighborhood inclusion rather than fixed distances. By adapting the metric based on the local structure of the data, it achieves superior neighborhood preservation, particularly for datasets with complex geometries and high-dimensional structures. Experimental results demonstrate that ALLE significantly improves the alignment between neighborhoods in the input and feature spaces, resulting in more accurate and topologically faithful embeddings. This approach advances manifold learning by tailoring distance metrics to the underlying data, providing a robust solution for capturing intricate relationships in high-dimensional datasets. © 2025, CC BY-SA.

关键词： Topology

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Effect of flexible spine on stability of a passive quadruped robot: Experimental results

Effect of flexible spine on stability of a passive quadruped...

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2011 IEEE International Conference on Robotics and Biomimetics, ROBIO 2011

作者： Kani, Mohammad Hasan H. Derafshian, Mostafa Bidgoly, Hamed Jalaly Ahmadabadi, Majid Nili Cognitive Robotics Lab. Control and Intelligent Processing Center of Excellence University of Tehran Iran

ISBN: (纸本)9781457721373

In rapid quadruped animals, the flexibility of spine is obviously observable while running. In this paper, we introduce a 3D passive dynamic quadruped robot, Fanari, that is capable to gallop down a slope without any external energy. We study the effect of spine flexibility on improvement of stability, adaptability and achievement of rapid leg locomotion. So a flexible spine that is capable to bend both outward and downward, a flexible spine that is only capable to bend outward and a rigid spine are designed and tested on the robot. Based on the case studies, we discuss about the challenges and the roles of spine stiffness on the gallop action. A simulation model is also made in order to corroborate the experimental results of the robot. It is concluded that the robot with the spine that is flexible in both outward and downward directions, has the most stability, adaptability and fastest velocity in its gallop action. © 2011 IEEE.

关键词： Multipurpose robots

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Improvement of low frequency oscillation damping in power systems via an adaptive critic based neurofuzzy controller 8th

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8th International Conference on Knowledge-Based intelligent Information and Engineering Systems, KES 2004

作者： Rashidi, Farzan Moshiri, Behzad Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Iran

ISBN: (纸本)9783540232056

This paper proposes an Adaptive Critic Based Neuro-Fuzzy controller (ACBNFC) to Thyristor controlled Series Capacitor (TCSC), which might have a significant impact on power system dynamics. The function of the ACBNFC is to control a firing angle of the TCSC. The proposed method is used for damping the low frequency oscillations caused by disturbances such as a sudden change of small or large loads or an outage in the generators or transmission lines. To evaluate the usefulness of the proposed method, the computer simulation for single machine infinite system is performed and compared with fuzzy PD controller. Obtained results show the proposed control strategy is very robust, flexible and could be used to get the desired performance levels. The response time is also very fast. Simulation results that have been compared with fuzzy PD controller show that our method has the better control performance than fuzzy PD controller. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Damping

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Land vehicle state estimation using a modified LOLIMOT algorithm

Land vehicle state estimation using a modified LOLIMOT algor...

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作者： Rezaie, J. Moshiri, B. Araabi, B. Control and Intelligent Processing Centre of Excellence University of Tehran Tehran Iran

ISBN: (纸本)9783902661265

Modelling unknown nonlinear dynamic process is an essential prerequisite for model-based state estimation. Fuzzy local linearization (FLL) is a useful divideand- conquer method for coping with complex problem such as data based nonlinear process modelling. In this paper first a modified local linear model tree (LOLIMOT) algorithm for nonlinear system modelling are proposed. Expectation maximization (EM) algorithm is used for local model estimation. Based on available information two commonly used state estimators, based on FLL models are presented, with an implementation on a land vehicle state estimation to validate the proposed method. The proposed method has better results for state estimation. Copyright © 2006 IFAC.

关键词： State estimation

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A new modified fuzzy TOPSIS for group decision making using fuzzy majority opinion based aggregation

A new modified fuzzy TOPSIS for group decision making using ...

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作者： Aghaie, Hamid Shafieezadeh, Soroosh Moshiri, Behzad School of ECE Control and Intelligent Processing Center of Excellence University of Tehran Iran

ISBN: (纸本)9789644634284

This paper presents a modified fuzzy TOPSIS method with a new distance measurement and a fuzzy majority opinion aggregator for a multi criteria decision making (MCDM) problem. The rating of each alternative and the weight of each criterion is described by linguistic terms which can be expressed in triangular fuzzy numbers. We introduce a new distance metric by using graded mean integration representation of triangular fuzzy numbers. The concept of majority opinion gives an overall opinion which synthesizes the opinions of the majority of the decision makers. Fuzzy majority opinion aggregator is used to make a consensual judgment synthesizing the individual opinions. To clarify our proposed method, a numerical example is discussed. Results show that our proposed algorithm is more advantageous in reflecting opinions of the majority of decision makers and also provides more confidence for their decisions. © 2011 AmirKabir Univ of Tech.

关键词： Linguistics

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A dynamic modeling of stock prices and optimal decision making using MVP theory

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作者： Rajabioun, Ramin Rahimi-Kian, Ashkan School of Electrical and Computer Engineering Control and Intelligent Processing Center of Excellence University of Tehran Tehran Iran

ISBN: (纸本)9789048123100

In this paper, first a precise mathematical model is obtained for four competing or cooperating companies' stock prices and then the optimal buy/sell signals are ascertained for five different agents which are trading in a virtual market and are trying to maximize their wealth over 1 trading year period. The model is so that gives a good prediction of the next 30th day stock prices. The companies used in this modeling are all chosen from Boston Stock Market. Genetic Programming (GP) is used to produce the predictive mathematical model. The interaction among companies and the effect imposed by each of five agents on future stock prices are also considered in our modeling. Namely, we have chosen eight companies in order that there is some kind of interrelation among them. Comparison of the GP models with Artificial Neural Networks (ANN) and Neuro-Fuzzy Networks (trained by the LoLiMoT algorithm) shows the superior potential of GP in prediction. Using these models;five players, each with a specific strategy and all with one common goal (wealth maximization), start to trade in a virtual market. We have also relaxed the short-sales constraint in our work. Each of the agents has a different objective function and all are going to maximize themselves. We have used Particle Swarm Optimization (PSO) as an evolutionary optimization method for wealth maximization. © 2009 Springer Netherlands.

关键词： Genetic programming

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Impulse noise removal based on long-range correlation in an image

Impulse noise removal based on long-range correlation in an ...

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2003 10th IEEE International Conference on Electronics, Circuits and Systems, ICECS2003

作者： Harandi, Mehrtash T. Araabi, Babak N. Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)0780381637

Images are often contaminated by impulse noise. The major drawback of median filtering and its variants -that are widely used for removing impulsive noise- is the blurring effect for large window sizes and low noise suppression for small window sizes. In this paper, an algorithm for removing impulse noise in images is proposed. The long-range correlation information in a competitive scheme is utilized to find the gray level of degraded pixels. The experimental results show that the performance of our method in removing impulse noise is better than that of most other state-of-the-art methods. © 2003 IEEE.

关键词： Impulse noise

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