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2011 20th European Conference on Circuit Theory and Design, ECCTD 2011

作者： Milik, Adam Pulka, Andrzej Institute of Electronics Department of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland

ISBN: (纸本)9781457706189

The paper presents a package of arithmetic operation synthesis dedicated to reconfigurable logic controllers programmed according to IEC1131 and EN61131. The program is compiled to hardware structure with a massive parallel processing. The developed method automatically allocates resources and operations. It controls resource usage and operation timing. Using mixed concept of operation allocation that considers operation timing and forms combinatorial chains of operations number of execution cycles can be reduced. Finally an example of PID controller implementation is considered and compared with previous manual implementations. Introducing the automatic implementation method allows flexible implementing the control algorithms. The maximal possible parallelism (limited only by the algorithm dependencies and available resources) is introduced. © 2011 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Uter aided diagnosis methods based on fractal and spatial series analysis for kidney CT images

Uter aided diagnosis methods based on fractal and spatial se...

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17th Annual Scientific Conference on Web Technology, New Media Communications and Telematics Theory Methods, Tools and Applications, EUROMEDIA 2012

作者： Udrea, Andreea I. Tanase, Mihai Department of Automatic Control and Computer Science University Politehnica of Bucharest Spl. Independentei Bucharest Romania

ISBN: (纸本)9789077381694

The goal of this paper is to present a set of algorithms developed based on fractal and spatial series analysis that can be applied to computer aided diagnosis for discrimination between normal and modified kidney tissue. These algorithms were tested on 120 computer tomography (CT) images of normal, benign and malign affected renal tissue. Two of the algorithms provide useful numerical results that can be gathered to form statistics and provide a classification of the kidney tissue in normal and malign affected, while the third method can be used for enhanced visualization that proves its usefulness in the case of images that can not be classified. The conclusions of the study on the selected set of CT images are that distinction between normal and malign tissues can be done with high accuracy and significantly better results are obtained from CT images taken with contrast substances while using the correlation dimension. The enhancing procedure can give insights on the problem at hand when the statistics fails.

关键词： Fractal dimension

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Considerations on incremental approach to hardware implementation of Smith-Waterman algorithm

Considerations on incremental approach to hardware implement...

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18th International Conference - Mixed Design of Integrated Circuits and Systems, MIXDES 2011

作者： Pulka, Andrzej Milik, Adam Institute of Electronics Department of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland

ISBN: (纸本)9788393207503

The paper presents optimized hardware structure applied to genome alignment search. The proposed methodology is based on dynamic programming. The authors show how starting from the original Smith-Waterman approach, the algorithm can be optimized and the evaluation process simplified and speeded-up. The main idea is based on the observations of growth trends in the adjacent cells of the systolic array, which leads to the incremental approach. Moreover various coding styles are discussed and the best technique allowing further reduction of resources is selected. The entire processing unit utilizes fully pipelined structure that is well balanced trade-off between performance and resource requirements. The proposed technique is implemented in modern FPGA structures and obtained results proved efficiency of the methodology comparing to other approaches in the field. © 2011 Tech Univ of Lodz.

关键词： Systolic arrays

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Observer-based finite-time control of conformable Takagi–Sugeno fuzzy systems with time delay

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Asian Journal of control 2025年

作者： Kahouli, Omar Gassara, Hamdi Aloui, Ali Elleuch, Zied Bouteraa, Yassine Department of Electronics Engineering Community College University of Ha'il Ha'il Saudi Arabia Laboratory of Science and Technology of Automatic Control and Computer Engineering National School of Engineering of Sfax University of Sfax Sfax Tunisia Department of Computer Science Community College University of Ha'il Ha'il Saudi Arabia Department of Computer Engineering College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University Al-Kharj Saudi Arabia

This paper examines finite-time (F-T) observer-based control of fractional-order nonlinear systems with time delay, employing the Takagi–Sugeno fuzzy (T-SF) approach. This study utilizes the conformable fractional derivative (CFD) as its foundational framework. Sufficient conditions are formulated to guarantee that the augmented vector, consisting of the state estimates and the state estimation errors, stays within a ball centered at the origin. This applies not only to specified initial conditions but also to predefined disturbances. These conditions are then reformulated as linear matrix inequalities (LMIs) conditions, which can be efficiently solved using the LMI toolbox. An illustrative example is given to illustrate the proposed result. © 2025 Chinese automatic control Society and John Wiley & Sons Australia, Ltd.

关键词： Delay-sensitive applications

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Handling New and Changing Requirements with Guarantees in Self-Adaptive Systems Using SimCA 12

Handling New and Changing Requirements with Guarantees in Se...

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12th IEEE/ACM International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2017

作者： Shevtsov, Stepan Weyns, Danny Maggio, Martina Department of Computer Science Linnaeus University Sweden Department of Computer Science KU Leuven Belgium Linnaeus University Sweden Department of Automatic Control Lund University Sweden

ISBN: (纸本)9781538615508

Self-adaptation provides a principled way to deal with change during operation. As more systems with strict goals require self-adaptation, the need for guarantees in self-adaptive systems is becoming a high-priority concern. Designing adaptive software using principles from control theory has been identified as one of the approaches to provide guarantees. However, current solutions can only handle pre-specified requirements either in the form of setpoint values (S-reqs) or values to be optimized (O-reqs). This paper presents SimCA∗ that makes two contributions to control-based self-adaptation: (a) it allows the user to specify a third type of requirement that keeps a value above/below a threshold (T-reqs), and (b) it can deal with requirement sets that change at runtime (i.e., requirements can be adjusted, activated, and deactivated on the fly). SimCA∗ offers robustness to disturbances and provides adaptation guarantees. We evaluate SimCA∗ for two systems with strict goals from different domains: an underwater vehicle system used for oceanic surveillance, and a tele-assistance system for health care support. The test results demonstrate that SimCA∗ can deal with the three types of requirements (STO-reqs) operating under various types of dynamics and the set of requirements can be changed on the fly. © 2017 IEEE.

关键词： control theory

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Multiway principal component analysis and case base reasoning methodology for abnormal situation detection in a nutrient removing SBR 9

Multiway principal component analysis and case base reasonin...

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2007 9th European control Conference, ECC 2007

作者： Garcia, M. Ruiz, M. Colomer, J. Melendez, J. Modal Interval Automatic Engineering Group - MICE Department of Electronics Computer Science and Automatic Control University of Girona CP 17071 Building PIV Girona Spain Control Engineering and Intelligent Systems Group EXiT Department of Electronics Computer Science and Automatic Control University of Girona CP 17071 Building PIV Girona Spain

ISBN: (纸本)9783952417386

Multiway Principal Component Analysis (MPCA) and Case-Based Reasoning (CBR) approaches are applied in a biological nutrient removal process. The goal of this study was to monitor of normal and abnormal operation conditions in this process. MPCA is used as a compression tool where, with a few variables, the process can be described, as well as, to detect batches with abnormal conditions. However, some false alarms were produced and others abnormal conditions were omitted. CBR is then proposed and it assumes that similar problems should have similar solutions. In biological process, these problems generally are operational situations under normal or abnormal situations: low ORP, high pH, sensors fault, among others. These symptoms can be stored in a Case Base (CB) in order to diagnose future situations. Several proof are made in order to improve the methodology. © 2007 EUCA.

关键词： Nutrients

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FAST-MODE REAL-TIME SIMULATOR FOR THE WASTE-WATER TREATMENT PROCESS

FAST-MODE REAL-TIME SIMULATOR FOR THE WASTE-WATER TREATMENT ...

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17th Biennial Conference of the International-Association-on-Water-Quality

作者： METZGER, M Department of Automatic Control Electronics and Computer Science Technical University of Silesia 44-100 Gliwice ul Akademicka 16 Poland

Process connected simulation of a process is very useful for optimal decision making. The problem of computer aided operator support in the case of a sudden augmentation of cyanide concentration in the inlet flow of a big industrial wastewater treatment plant is presented in the work. By using simulation experiments the operator of the process may check the consequences of the operating control strategies before the emergency in the real-world process occurs.

关键词： computer AIDED OPERATOR control computer SIMULATION control OF INDUSTRIAL WASTE-WATER TREATMENT PROCESS OPERATING control STRATEGIES REAL-TIME SIMULATION

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Distributed robustness analysis of interconnected uncertain systems using chordal decomposition 19

Distributed robustness analysis of interconnected uncertain ...

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19th IFAC World Congress on International Federation of automatic control, IFAC 2014

作者： Pakazad, Sina Khoshfetrat Hansson, Anders Andersen, Martin S. Rantzer, Anders Division of Automatic Control Department of Electrical Engineering Linköping University Sweden Department of Applied Mathematics and Computer Science Technical University of Denmark Denmark Department of Automatic Control Lund University Sweden

ISBN: (纸本)9783902823625

Large-scale interconnected uncertain systems commonly have large state and uncertainty dimensions. Aside from the heavy computational cost of performing robust stability analysis in a centralized manner, privacy requirements in the network can also introduce further issues. In this paper, we utilize IQC analysis for analyzing large-scale interconnected uncertain systems and we evade these issues by describing a decomposition scheme that is based on the interconnection structure of the system. This scheme is based on the so-called chordal decomposition and does not add any conservativeness to the analysis approach. The decomposed problem can be solved using distributed computational algorithms without the need for a centralized computational unit. We further discuss the merits of the proposed analysis approach using a numerical experiment. © IFAC.

关键词： Uncertain systems

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Optimizing Artificial Neural Networks Trough Weight Adjustments 28th

Optimizing Artificial Neural Networks Trough Weight Adjustme...

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28th International Conference on Knowledge Based and Intelligent information and Engineering Systems, KES 2024

作者： Akber, Syed Muhammad Abrar Szczesna, Agnieszka Kazmi, Sadia Nishat Department of Computer Graphics Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice44-100 Poland Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice44-100 Poland

Longer training times pose a significant challenge in artificial neural networks (ANNs) as it may leads to increasing the computational costs and decreasing the effectiveness of the model. Therefore, it is imperative to reduce training times in ANNs to enhance the computational efficiency. The initialization of the weights between the layers in ANN plays a vital role in reducing training times. Appropriate weight initialization can help the network converge faster during the training by providing an optimum starting point for the network. Therefore, weight initialization techniques are essential for efficient training of ANNs. This paper revisits and implements different popular weight initialization techniques in ANNs and analyzes their impact on training time. Specifically, this paper implements Gaussian-based, Kaming-based, and Xavier-based weight initiation atop a popular DNN-based network. The experiments are conducted by employing a well-known dataset. The results show that the scenario when no weight initiation is applied consumed the highest training time, whereas different weight initiation techniques contribute in reducing the training times for the network. © 2024 The Authors.

关键词： Deep neural networks

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Optimizing matrix mapping with data dependent kernel for image classification

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Journal of Information Hiding and Multimedia Signal Processing 2014年第1期5卷 72-79页

作者： Zhang, De-Long Qiao, Jiaqing Li, Jun-Bao Qiao, Li-Yan Chu, Shu-Chuan Roddick, John F. Department of Automatic Test and Control Harbin Institute of Technology China School of Computer Science Engineering and Mathematics Flinders University GPO Box 2100 Adelaide SA 5001 Australia

Kernel based nonlinear feature extraction is feasible to extract the feature of image for *** current kernel-based method endures two problems: 1) kernel-based method is to use the data vector through transforming the image matrix into vector, which will cause the store and computing burden;2) the parameter of kernel function has the heavy influences on kernel based learning method. In order to solve the two problems, we present the method of optimizing matrix mapping with data dependent kernel for feature extraction of the image for classification. The method implements the algorithm without transforming the matrix to vector, and it adaptively optimizes the parameter of kernel for nonlinear mapping. The comprehensive experiments are implemented evaluate the performance of the algorithms. © 2014.

关键词： Matrix algebra

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