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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Yousef Salimpour Hamid Soltanian-Zadeh Mohammad D. Abolhassani Neuroscience and Neuroengineering in School of Cognitive Sciences Institute of Studies in Fundamental Sciences IPM and Research Group for Brain and Cognitive Sciences School of Medicine Shahid Beheshti University Tehran Iran Department of Radiology Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence CIPCE Department of Electrical and Computer Engineering University of Tehran Tehran Iran Tehran University of Medical Sciences Tehran Tehran IR

A temporal point process is a stochastic time series of binary events that occurs in continuous time. In computational neuroscience, the point process is used to model neuronal spiking activity; however, estimating the model parameters from spike train is a challenging problem. The state space point process filtering theory is a new technique for the estimation of the states and parameters. In order to use the stochastic filtering theory for the states of neuronal system with the Gaussian assumption, we apply the extended Kalman filter. In this regard, the extended Kalman filtering equations are derived for the point process observation. We illustrate the new filtering algorithm by estimating the effect of visual stimulus on the spiking activity of object selective neurons from the inferior temporal cortex of macaque monkey. Based on the goodness-offit assessment, the extended Kalman filter provides more accurate state estimate than the conventional methods.

关键词： Mathematical model Equations Kalman filters Neurons Computational modeling Estimation

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Evolutionary Prisoner＇s Dilemma Game Based on Pursuing Higher Average Payoff

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Chinese Physics Letters 2009年第1期26卷 360-363页

作者：李玉金汪秉宏杨涵新凌翔陈小杰姜锐 Department of Modern Physics University of Science and Technology of China Hefei 230026 Shanghai Academy of System Science and University of Shanghai for Science and Technology Shanghai 200093 Faculty of Science Zhefiang Normal University Jinhua 321004 School of Engineering Science University of Science and Technology of China Hefei 230026 Intelligent Control Laboratory Center for Systems and Control Department of Mechanics and Space Technologies College of Engineering Peking University Beijing 100871

We investigate the prisoner＇s dilemma game based on a new rule： players will change their current strategies to opposite strategies with some probability if their neighbours＇ average payoffs are higher than theirs. Compared with the cases on regular lattices （RL） and Newman-Watts small world network （NW）, cooperation can be best enhanced on the scale-free Barabasi-Albert network （BA）. It is found that cooperators are dispersive on RL network, which is different from previously reported results that cooperators will form large clusters to resist the invasion of defectors. Cooperative behaviours on the BA network are discussed in detail. It is found that large-degree individuals have lower cooperation level and gain higher average payoffs than that of small-degree individuals. In addition, we find that small-degree individuals more frequently change strategies than do large- degree individuals.

关键词： PRISONER'S dilemma game BRIBERY MILITARY strategy LATTICE theory GAME theory MATHEMATICAL models

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Flow-rate Characteristics Measurement of Regulators Based on the Pressure Response in an Isothermal Tank

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Chinese Journal of Mechanical engineering 2009年第5期22卷 633-638页

作者： FAN Wei ZHANG Hongli WANG Tao PENG Guangzheng ONEYAMA Naotake Education Ministry Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing 100081 China School of Automation Beijing Institute of Technology Beijing 100081 China Electrical Engineering College Xinjiang University Urumchi 830046 China SMC Tsukuba Technical Center Ibaraki-ken 300-2493 Japan

Regulators are important components in pneumatic system, and their flow-rate characteristics are the key parameters for designers. According to the correlatively international standard and national standard of China, which describe the flow-rate characteristics measurement method of pneumatic regulators, the pressure and the flow are measured point by point, and then the flow-rate characteristics curve is plotted point to point. This method has some disadvantages, such as equipment complexity, much air consumption, and low efficiency. To settle the problems presented above, this paper puts forward a new high efficient and energy saving flow-rate characteristics measurement method of regulators, which is based on the pressure response when charging and discharging to an isothermal tank without any flow meters. The measurement principle, the system and the steps are introduced. And the tracking differentiator is used for the data processing of the pressure difference. Two typical kinds of regulators were experimentally investigated, and their flow-rate characteristics curves were obtained with the new and the conventional method, respectively. Comparatively, it＇s proved that this new method is feasible because it is not only able to meet the demand of the measurement precision, but also to save energy and improve efficiency. Compared to the conventional method, the new method takes only about 1/10 amount of time and consumes about only 1/30 amount of air. Hopefully it will be able to serve as an international standard of flow-rate characteristics measurement method of regulators.

关键词： regulator flow-rate characteristics isothermal tank charging and discharging once pressure response tracking differentiator energy saving and high efficiency

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Particle filtering of point processes observation with application on the modeling of visual cortex neural spiking activity

Particle filtering of point processes observation with appli...

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International IEEE/EMBS Conference on Neural engineering, CNE

作者： Yousef Salimpour Hamid Soltanian-Zadeh Computational Neuroscience in School of Cognitive Sciences Institute of Studies in Fundamental Sciences Tehran Iran Department of Radiology Henry Ford Health System Detroit MI USA Control and Intelligent Processing Center of Excellence(CIPCE) Department of Electrical and Computer Engineering University of Tehran Tehran Iran

Recording of neural response to specific stimulus in a repeated trial is very common in neuroscience protocol. The perstimulus time histogram (PSTH) is a standard tool for analysis of neural response. However it could not capture the non-deterministic properties of the neuron especially in higher level cortical area such as inferior temporal cortex. The stochastic state point process filter theory is used for the estimation of the conditional intensity of the point process observation as a time varying firing rate and the particle filter is used to numerically estimate this density in time. The particle filters were applied to the results of the point process observation for compensating the Gaussian assumption. The results of applying point process modeling on a real data from inferior temporal cortex of macaque monkey indicates that, based on the assessment of goodness-of-fit, the neural spiking activity and biophysical property of neuron could be captured more accurately in compare to conventional methods.

关键词： Filtering Brain modeling Neurons Stochastic processes State estimation Particle filters Histograms Mathematical model Neural engineering Neuroscience

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Robust controller Design for Networked control systems with Nonlinear Uncertainties

Robust Controller Design for Networked Control Systems with ...

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2009 American control Conference (ACC 2009)

作者： Junyan Yu Long Wang Mei Yu Jie Chen Yingmin Jia Intelligent Control Laboratory Center for Systems and Control College of Engineering and Key Laboratory of Machine Perception (Ministry of Education) Peking University Beijing 100871 P.R.China Department of Automation North China Electric Power University Zhuxinzhuang Dewai Beijing 102206 P.R.China Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing 100081 P.R.China Seventh Research Division Beihang University Beijing 100083 P.R. China

ISBN: (纸本)9781424445233

We address robust stabilization problem for networked control systems with nonlinear uncertainties and packet losses by modelling such systems as a class of uncertain switched systems. Based on theories on switched Lyapunov functions, we derive the robustly stabilizing conditions for state feedback stabilization and design packet-loss dependent controllers by solving some matrix inequalities. A numerical example and some simulations are worked out to demonstrate the effectiveness of the proposed design method.

关键词： Networked control systems robust controller design Packet loss control systems design approach Switched systems controller design State feedback Uncertainty nonlinearity

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Stabilizability of Networked control systems via Packet-loss Dependent Output Feedback controllers

Stabilizability of Networked Control Systems via Packet-loss...

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2008 American control Conference (ACC), vol.9

作者： Junyan Yu Long Wang Mei Yu Yingmin Jia Jie Chen Intelligent Control Laboratory Center for Systems and Control College of Engineering Peking University Beijing China Department of Automation North China Electric Power University Beijing China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing China

We consider the output feedback stabilizability of networked control systems with bounded packet loss. A packet-loss dependent Lyapunov function is adopted to design packet-loss dependent stabilizing output feedback controllers by resolving some linear matrix inequalities. Moreover, two types of packet-loss processes are discussed: one is the arbitrary packet-loss process, and the other is the Markovian packet-loss process. A numerical example and some simulations are worked out to demonstrate the effectiveness of the proposed design technique.

关键词： Networked control systems Output feedback control systems Switched systems State feedback Lyapunov method Linear matrix inequalities Electrical equipment industry Industrial control Sufficient conditions

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Packet-loss dependent controller design for networked control systems via switched system approach

Packet-loss dependent controller design for networked contro...

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IEEE Conference on Decision and control

作者： Junyan Yu Long Wang Mei Yu Yingmin Jia Jie Chen Intelligent Control Laboratory Center for Systems and Control College of Engineering Peking University Beijing China Department of Automation North China Electric Power University Zhuxinzhuang Beijing China The Seventh Research Division Beihang University Beijing China Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing China

ISBN: (纸本)9781424431236

The stabilization problem of networked control systems with bounded packet loss is addressed. We model such networked control systems as a class of switched systems, and present sufficient conditions for the stabilization by using a packet-loss dependent Lyapunov function. Moreover, different from existing results, we propose the design for packet-loss dependent stabilizing controllers for two types of packet-loss processes: one is a arbitrary packet-loss process, and the other is a Markovian packet-loss process. Several numerical examples and simulations are worked out to demonstrate the effectiveness of the proposed design technique.

关键词： control systems Networked control systems Switched systems Sufficient conditions Optimal control Delay effects Communication system control Communication system traffic control Feedback control Electrical equipment industry

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Feature fusion as a practical solution toward noncooperative iris recognition

Feature fusion as a practical solution toward noncooperative...

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International Conference on Information Fusion

作者： Nima Tajbakhsh Babak N. Araabi Hamid Soltanianzadeh Control & Intelligent Processing Center of Excellence School of Electrical & Computer Engineering University of Tehran Tehran Iran School of Cognitive Sciences Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI USA

In noncooperative Iris recognition one should deal with uncontrolled behavior of the subject as well as uncontrolled lighting conditions. That means imperfect focus, contrast, brightness, and orientation among the others. To cope with this situation we propose to take iris images at both near infrared (NIR) and visible light (VL) and use them simultaneously for recognition. In this paper, a novel approach for iris recognition is proposed so that extracted features of NIR and VL images are fused to improve the recognition rate. When the images do not have enough quality due to focus, contrast, etc., effects of feature fusion is more pronounced. This is the situation in UTIRIS database, which is used in our experiments. Experimental results show that the proposed approach, especially in small training samples, leads to a remarkable improvement on recognition rate compared with either NIR or VL recognition.

关键词： Iris Feature extraction Discrete cosine transforms Image recognition Databases Training Humans

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Constrained optimization of nonparametric entropy-based segmentation of brain structures

Constrained optimization of nonparametric entropy-based segm...

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IEEE International Symposium on Biomedical Imaging

作者： Alireza Akhondi Asl Hamid Soltanian-Zadeh School of Cognitive Sciences Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI USA

We propose a constrained, three-dimensional, nonparametric, entropy-based, coupled, multi-shape approach to segment subcortical brain structures from magnetic resonance images (MRI). The proposed method uses PCA to develop shape models that capture structural variability. It integrates geometrical relationship between different structures into the algorithm by coupling them (limiting their independent deformations). On the other hand, to allow variations among coupled structures, it registers each structure separately when building the shape models. It defines an entropy-based energy function, which is minimized using quasi-Newton algorithm. To this end, probability density functions (pdf) are estimated iteratively using nonparametric Parzen window method. In the optimization algorithm, constraints are used to improve segmentation quality. These constraints are extracted from training data. Sample results are given for the segmentation of caudate, hippocampus, and putamen, illustrating highly superior performance of the proposed method compared to the most similar methods in the literature.

关键词： Constraint optimization Brain Iterative algorithms Image segmentation Shape Couplings Magnetic resonance Magnetic resonance imaging Principal component analysis Buildings

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Towards an inclusive computational model of visual cortex

Towards an inclusive computational model of visual cortex

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： M. Gheiratmand H. Soltanian-Zadeh H. Khaloozadeh Electrical Engineering Department K.N. Toosi University of Technology Tehran Iran Radiology Department Henry Ford Health System Image Analysis and Communications Laboratory Detroit MI USA School of Cognitive Sciences Institute for Studies Theoretical Physics and Mathematics (IPM) Tehran Iran Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Tehran Iran

Understanding the primatespsila visual system has been one of the challenging problems of different groups of scientists for years. Though many studies, from physiology and neuroscience to computer vision, are done on different aspects of visual processing in the cortex, a comprehensive computational model of visual cortex is still missing. We have implemented a computational model of object recognition in ventral visual pathway in our previous work. This hierarchical model covers visual areas V1/V2, V4/PIT, and AIT sending inputs to the Prefrontal Cortex (PFC) for categorization. To extend our model, in this work, we have added a simple model of motion detection in neurons of areas V1 and MT of the dorsal stream to our previous model. This has enabled the model to perform another principal function of the visual cortex, i.e., motion perception.

关键词： Brain modeling Computational modeling Neurons Biological system modeling Object recognition Motion analysis Solid modeling Visual system Computer vision Motion detection

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