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 s...
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In this paper, a new approach to enlarge the domain of attraction of a nonlinear affine system based on Zubov Theorem is suggested. The affine systems which are studied in this paper some times have some constraints t...
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In this paper, system identification and neural network predictive control (NNPC) of a continuous stirred tank reactor (CSTR) is presented. The control problem with the objective of set point tracking between several ...
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A game is a decision-making situation in which each player attempts to act in such a way that the game's circumstances get close to what desirable for him. To reach this goal, a player needs to have a suitable est...
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Game theory deals with decision-making processes involving two or more parties with partly or completely conflicting interests. The players involved in the game usually make their decisions under conditions of risk or...
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We present a general mathematical description of the top-down attention control problem. Three important components are identified in the model: context extraction, attention focus and decision making. The context giv...
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We present a general mathematical description of the top-down attention control problem. Three important components are identified in the model: context extraction, attention focus and decision making. The context gives a coarse blurry representation of the whole input;the attention module models the focus of attention on a limited part of input, and the decision making component accounts the final decision of the agent for its motory actions. In order to achieve a faster convergence of attention learning in the online phase, an offline optimization step is performed in advance. To do so, we incorporate the knowledge of a full observer agent that has approximately learned the optimal decision making of the task. The simulation results show that by employing our algorithm, the learning speed is improved.
This paper presents the results of automated classifying Farsi text documents using tri-gram, quad-gram, and word frequency statistics methods. Three similarity/dissimilarity measures, namely, "Manhattan Distance...
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ISBN:
(纸本)1601320620
This paper presents the results of automated classifying Farsi text documents using tri-gram, quad-gram, and word frequency statistics methods. Three similarity/dissimilarity measures, namely, "Manhattan Distance", "Dice measure", and "Dot Product" are used for comparison purpose. K-nearest neighbors learning technique is employed and effects of removing or maintaining stop words are also studied. Results, stated in terms of precision and recall, show that applying quad-grams using dot product similarity measure while stop words are omitted, gives the best result among all of the combinations of the applied methods.
This paper presents a systematic design procedure of fuzzy controllers for exponentially stabilizing affine nonlinear systems, which are subject to vanishing perturbations. The modeling error, as a key factor in the v...
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Nowadays, there are considerable attentions to combined classifier. Recently, the focus has been shifting from practical heuristic solutions of combination methods to give a methodological way of design. In this study...
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ISBN:
(纸本)0662478304
Nowadays, there are considerable attentions to combined classifier. Recently, the focus has been shifting from practical heuristic solutions of combination methods to give a methodological way of design. In this study a co-evolutionary algorithm is presented for this purpose. The algorithm synthesizes an explicit classifier directly from bserved data produced by intelligently generated tests. The algorithm is composed of two co-evolving populations;one population evolves candidate classifiers. The second population evolves informative tests that either extract new information from the pattern or elicit desirable behavior from it. The fitness of candidate classifiers is their ability to classify in response to all tests carried out so far;the fitness of candidate tests is their ability to make the classifiers disagree in their classifications. The generality of this modeling-evaluation algorithm is demonstrated by applying the chosen classifier of this algorithm to identify modulation methods and results depict the power of this algorithm.
Speckle noise reduction is the first and important step for intravascular ultrasound (IVUS) image analysis. A comparison between the performances of the curvelet transform and adaptive complex diffusion filter method ...
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