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检索条件"机构=Pattern Analysis and Machine Intelligence Laboratory Systems Design Engineering"

共 79 条记录，以下是51-60 订阅

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Quasi-global oppositional fuzzy thresholding

Quasi-global oppositional fuzzy thresholding

引用

IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： Hamid R. Tizhoosh Farhang Sahba Pattern Analysis and Machine Intelligence Laboratory Systems Design Engineering University of Waterloo Waterloo ONT Canada University of Toronto Toronto ONT Canada

Opposition-based computing is the paradigm for incorporating entities along with their opposites within the search, optimization and learning mechanisms. In this work, we introduce the notion of "opposite fuzzy sets" in order to use the entropy difference between a fuzzy set and its opposite to carry out object discrimination in digital images. A quasi-global scheme is used to execute the calculations, which can be employed by any other existing thresholding technique. Results for prostate ultrasound images have been provided to verify the performance whereas expert's markings have been used as gold standard.

关键词： Fuzzy sets Image segmentation Fuzzy systems machine intelligence Ultrasonic imaging Neural networks pattern analysis Laboratories System analysis and design design engineering

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Software architecture for real-time autonomous agents: a case study for digital train system

Software architecture for real-time autonomous agents: a cas...

引用

IEEE International Symposium on Intelligent Control (ISIC)

作者： Insop Song F. Karray PAMI (Pattern Analysis Machine Intelligence) Group Department of Systems Design Engineering University of Waterloo Waterloo ONT Canada

In this paper, a software architecture for multiple autonomous agents in a real-time environment is described. The software architecture for autonomous agents must effectively connect perception modules, planning modules and action modules. It is necessary to define both an interface and a data flow among different modules. The proposed software architecture connects reactive modules with deliberative modules. The architecture proved its feasibility by controlling a prototype of multiple model digital trains.

关键词： Software architecture Real time systems Autonomous agents Computer aided software engineering Computer architecture Switches Mobile robots Communication system control Computer errors pattern analysis

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Observer-dependent sharpening

Observer-dependent sharpening

引用

IEEE International Conference on Image Processing

作者： H.R. Tizhoosh Pattern Recognition and Machine Intelligence Laboratory Systems Design Engineering University of Waterloo Waterloo ONT Canada

Image quality evaluation by human observers is heavily subjective in nature. Individual observers judge the image quality differently. In previous works, an observer-dependent system for subjective image enhancement, which is based on fusion of different algorithms, was introduced. In this paper, the system configuration for sharpness/smoothness is discussed and experimental results are provided.

关键词： Image enhancement Image quality Humans pattern recognition machine intelligence design engineering systems engineering and theory Image processing Man machine systems Convolution

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RBF-based real-time hierarchical intrusion detection systems

RBF-based real-time hierarchical intrusion detection systems

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Ju Jiang Chunlin Zhang M. Kamel Pattern Analysis and Machine Intelligence Research Group Systems Design Department Engineering Faculty University of Waterloo Canada Systems Design Department University of Waterloo Canada

An intrusion detection system (IDS) is an art to detect network intrusions by monitoring the network traffic patterns. Generally, an IDS uses only a single-layer detection structure; therefore it cannot adjust its structure adaptively and automatically. In this paper, two hierarchical IDSs, the serial hierarchical and parallel hierarchical IDSs, are proposed. Both of them are based on radial basis function (RBF) neural networks. Because of the short training time and high accuracy of the RBF neural networks, two hierarchical IDSs can monitor network traffic in real-time, train new classifiers for novel intrusions automatically, and modify their structures adaptively after new classifiers are trained.

关键词： Real time systems Intrusion detection Neural networks Telecommunication traffic Computerized monitoring Computer networks Condition monitoring pattern analysis machine intelligence System analysis and design

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Opposition-Based Q(λ) with Non-Markovian Update

Opposition-Based Q(λ) with Non-Markovian Update

引用

IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, (ADPRL)

作者： Maryam Shokri Hamid R. Tizhoosh Mohamed S. Kamel Pattern Analysis and Machine Intelligence Laboratory Department of Systems Design Engineering University of Waterloo ONT Canada Department of Electrical and Computer Engineering University of Waterloo ONT Canada

The OQ(λ) algorithm benefits from an extension of eligibility traces introduced as opposition trace. This new technique is a combination of the idea of opposition and eligibility traces to deal with large state space problems in reinforcement learning applications. In our previous works the comparison of the results of OQ(λ) and conventional Watkins' Q(λ) reflected a remarkable increase in performance for the OQ(λ) algorithm. However the Markovian update of opposition traces is an issue which is investigated in this paper. It has been assumed that the opposite state can be presented to the agent. This may limit the usability of the technique to deterministic environments. In order to relax this assumption the non-Markovian opposition-based Q(λ) (NOQ(λ)) is introduced in this work. The new method is a hybrid of Markovian update for eligibility traces and non-Markovian-based update for opposition traces. The experimental results show improvements of learning speed for the proposed technique compared to Q(λ) and OQ(λ). The new technique performs faster than OQ(λ) algorithm with the same success rate and can be employed for broader range of applications since it does not require determining state transition

关键词： Learning Usability Dynamic programming pattern analysis machine intelligence Laboratories System analysis and design design engineering systems engineering and theory State-space methods

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Improving gradient-based learning algorithms for large scale feedforward networks

Improving gradient-based learning algorithms for large scale...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： M. Ventresca H. R. Tizhoosh Faculty member of the Pattern Analysis and Machine Intelligence laboratory and Opposition-Based Learning Groups in the Systems Design Engineering Department University of Waterloo Waterloo ONT Canada

Large scale neural networks have many hundreds or thousands of parameters (weights and biases) to learn, and as a result tend to have very long training times. Small scale networks can be trained quickly by using second-order information, but these fail for large architectures due to high computational cost. Other approaches employ local search strategies, which also add to the computational cost. In this paper we present a simple method, based on opposite transfer functions which greatly improve the convergence rate and accuracy of gradient-based learning algorithms. We use two variants of the backpropagation algorithm and common benchmark data to highlight the improvements. We find statistically significant improvements in both convergence speed and accuracy.

关键词： Large-scale systems Transfer functions Neural networks Feedforward neural networks Computer architecture Computational efficiency Convergence Backpropagation algorithms Computer networks design engineering

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Fuzzy clustering neural network system design and implementation

Fuzzy clustering neural network system design and implementa...

引用

Midwest Symposium on Circuits and systems (MWSCAS)

作者： D. Zhang M. Kamel M.I. Elmasry Electrical and Computer Engineering VLSI Research Group Pattern Analysis and Machine Intelligence Systems Design Engineering University of Waterloo Waterloo ONT Canada

In this paper, a novel VLSI system design methodology for fuzzy clustering neural networks (FCNN) is presented. This methodology emphasizes a coordination between model definition, architectural description, and hardware implementation, Two mapping strategies, from FCNN model to parallel architecture and from architecture to systolic implementation, are discussed. The system design is achieved by 1) developing an effective FCNN model, where a direct fuzzy competitive learning algorithm between the nodes is adopted; 2) designing the corresponding parallel architecture with special feedforward and feedback paths; 3) building the systolic array (SA) suitable for VLSI.

关键词： Fuzzy neural networks Fuzzy systems Neural networks Very large scale integration System analysis and design design engineering Hardware Clustering algorithms Systolic arrays Computational modeling

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A fuzzy set approach to extracting keywords from abstracts

A fuzzy set approach to extracting keywords from abstracts

引用

Conference of the North American Fuzzy Information Processing Society - NAFIPS

作者： M. Makrehchi M. Kamel Pattern Analysis and Machine Intelligence Lab Department of Systems Design Engineering University of Waterloo Waterloo ONT Canada Department of Systems Design Engineering University of Waterloo Waterloo Ontario Canada

An unsupervised keyword extraction method based on corpora is proposed. After representing each document in the collection by a fuzzy set of candidate keywords, the problem is translated into finding appropriate fuzzy membership degree for each candidate. In order to determine the membership degrees, first, all terms of the vocabulary are mapped into a two-dimensional space called class-collection map by obtaining two newly proposed fuzzy measures called fuzzy significance and fuzzy relevance for each term. At the second step, the mapped terms are grouped into three categories, namely, features, keywords and stopwords that are discriminated by their contribution to the meaning of the documents. Instead of a clustering approach for grouping purpose, a fuzzy rule base is provided. The method is independent of the language and data dimensionality. It does not require the use of dictionary, thesaurus nor natural language processing.

关键词： Fuzzy sets Vocabulary Web pages Abstracts Text mining Fuzzy systems pattern analysis machine intelligence System analysis and design design engineering

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A novel computational intelligence approach for multiple-point routing in communication networks

A novel computational intelligence approach for multiple-poi...

引用

IEEE International Conference on systems, Man and Cybernetics

作者： S. Al-Sharhan F. Karray W. Gueaieb Department of Systems Design Engineering University of Waterloo Ontario Canada Pattern Analysis and Machine Intelligence (PAMI) Lab Department of Systems Design Engineering University of Waterloo Waterloo ONT Canada

A new evolutionary algorithm for the constrained multiple destination routing problem is presented. The constrained multicast problem is characterized by a minimum cost multicast tree and a bounded end-to-end delay. It has been proven that this problem is NP-complete. The proposed algorithm is based on a soft computing technique that integrates in an efficient manner the merits of genetic algorithms and concepts of the competitive learning in the artificial neural networks literature. A population based learning algorithm is utilized, among other techniques, to construct a delay bounded multicast tree. A salient feature of the algorithm is the adaptive learning concept that achieves an efficient trade-off between the exploration and exploitation of the search space.

关键词： Computational intelligence Routing Communication networks Multicast algorithms Delay Evolutionary computation Costs Computer networks Genetic algorithms Artificial neural networks

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Real world implementation of fuzzy anti-swing control for behavior-based intelligent crane system

Real world implementation of fuzzy anti-swing control for be...

引用

IEEE International Workshop on Intelligent Robots and systems (IROS)

作者： Jiaming Wang Hao Li F. Karray O. Basir PAMIR Pattem Analysis Machine Intelligence and Robotics Laboratory Systems Design Engineering University of Waterloo Waterloo ONT Canada

There exist several industrial applications for large crane systems. Most of them experience serious problems with load swing. This paper presents a fuzzy based control scheme to minimize load swing for crane systems while maintaining continuous payload transportation. The control system of the crane is built using behavior-based approaches. In the control system developed, each module generates behaviors, and improvement in the performance of the system proceeds by adding new modules to the system. In order to develop the anti-swing module, fuzzy logic controller is applied using information extracted from potentiometers. The fuzzy controller provides a mechanism for dealing with imprecise sensor data. The anti-swing behaviors are successfully implemented by formulating a set of fuzzy rules. The performance of the developed system is illustrated by both simulations and experiments. The simulation and experimental results of the system show that the system remains stable under several operating situations.

关键词： Fuzzy control Fuzzy systems Control systems Intelligent systems Intelligent control Cranes Electrical equipment industry Payloads Transportation Fuzzy logic

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