Cross-correlation of complex, picosecond-range, temporal shapes is demonstrated experimentally with the help of a filter recorded in an organic spectral hole-burning material.
Cross-correlation of complex, picosecond-range, temporal shapes is demonstrated experimentally with the help of a filter recorded in an organic spectral hole-burning material.
In order to maximize the available performance of the Li-ion batteries, a searching algorithm for an optimal fast charging pattern using particle swarm optimization (PSO) with an evaluation index based on the fuzzy-de...
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ISBN:
(纸本)9781467327435;9781467327428
In order to maximize the available performance of the Li-ion batteries, a searching algorithm for an optimal fast charging pattern using particle swarm optimization (PSO) with an evaluation index based on the fuzzy-deduced cost function is proposed in this paper. An optimal five-stage charging strategy is obtained by the PSO searching according to the decision-making in the fitness evaluation index that is computed from the cost function. The cost function formulated by two paramount parameters, charge time and discharge capacity, is employed to assess the cost benefit of the applied charging pattern. Regulating rules of weighting within the cost function are derived from the fuzzy logic inference to attain the best fitness evaluation. The proposed searching methodology for optimal multistage charging pattern features characteristics of fast convergence, effectiveness and easy to implement. Experimental results show that the obtained rapid charging pattern is capable of charging the batteries to 90% available capacity within 51 minutes and also provides 22% more cycle life than the conventional constant current-constant voltage (CC-CV) method.
Data raining and knowledge discovery is described from patternrecognition point of view along with the relevance of softcomputing. The concept of computational theory of perceptions (CTP), its characteristics and th...
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ISBN:
(纸本)9783540774433
Data raining and knowledge discovery is described from patternrecognition point of view along with the relevance of softcomputing. The concept of computational theory of perceptions (CTP), its characteristics and the relation with fuzzy-granulation (f-granulation) are explained. Role of f-granulation in machine and human intelligence, and its modeling through rough-fuzzy integration are discussed. Three examples of synergistic integration, e.g., rough-fuzzy case generation, rough-fuzzy c-means and rough-fuzzy c-medoids are explained with their merits and role of fuzzy granular computation. Superiority, in terms of performance and computation time, is illustrated for the tasks of case generation (mining) in large scale case based reasoning systems, segmenting brain MR images, and analyzing protein sequences.
In this work, a fast approximate nearest neighbour search algorithm using single Space-filling Curve (SPFC) Mapping and a set of synthetic prototype representations is presented. The results are comparable to a multip...
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ISBN:
(纸本)0769525210
In this work, a fast approximate nearest neighbour search algorithm using single Space-filling Curve (SPFC) Mapping and a set of synthetic prototype representations is presented. The results are comparable to a multiple-spacefilling scheme, but achieving a much faster execution time, since computing multiple transformations and SPFC Mapping's is avoided, at the expense of having a more densely populated one-dimensional representation of the data-set. The advantages and limitations of the model are discussed, and an experimental evaluation with synthetic data and with a large, real high-dimensional optical character recognition data-set is presented.
We study the domain of dominant competence of six popular classifiers in a space of data complexity measurements. We observe that the simplest classifiers, nearest neighbor and linear classifier have extreme behavior ...
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ISBN:
(纸本)0769521282
We study the domain of dominant competence of six popular classifiers in a space of data complexity measurements. We observe that the simplest classifiers, nearest neighbor and linear classifier have extreme behavior of being the best for the easiest and the most difficult problems respectively, while the sophisticated ensemble classifiers tend to be robust for wider types of problems and are largely equivalent in performance. We characterize such behavior in detail using the data complexity metrics, and discuss how such a study can be matured for providing practical guidelines in classifier selection.
Edge detection has been used in many applications such as image analysis, patternrecognition and computer vision. Various edge detection techniques are used in images to filter out less relevant information while pre...
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ISBN:
(纸本)9781467379182
Edge detection has been used in many applications such as image analysis, patternrecognition and computer vision. Various edge detection techniques are used in images to filter out less relevant information while preserving the basic structural properties in different domains. In this paper a critical evaluation of various edges detection techniques with softcomputing techniques has been examined.
A self-organizing map (SOM) can be seen as an analytical tool to discover some underlying rules in the given data set. Based on such distinctive nature called topology-preserving projection, a new method for generatin...
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ISBN:
(纸本)9781467327435;9781467327428
A self-organizing map (SOM) can be seen as an analytical tool to discover some underlying rules in the given data set. Based on such distinctive nature called topology-preserving projection, a new method for generating intermediate patterns was proposed. According to the results of preceding studies, most developed patterns are notmorphing but dissolve. Then, in order to overcome this problem, a fragmentized distance measure is introduced in this paper. As a result of computer simulations, it is confirmed that some asymmetrical patterns are developed even though only symmetrical ones are used for training. This fact reminds us that the distance measure is quite essential, because a feature map is developed through training based on the distance measure.
The proceedings contain 71 papers. The topics discussed include: complementary place transformation in Petri nets;a review on load balancing for reducing congestion in mobile ad-hoc networks;precision driven privacy-p...
ISBN:
(纸本)9781538645529
The proceedings contain 71 papers. The topics discussed include: complementary place transformation in Petri nets;a review on load balancing for reducing congestion in mobile ad-hoc networks;precision driven privacy-preserving anonymization for social data using segmentation;design and modeling of high power DC-DC boost converter for solar photovoltaic system;an enhanced approach of genetic and ant colony based load balancing in cloud environment;evaluation of human age with FKP using K-NN;an investigation approach used for pattern classification and recognition of an emergency vehicle;and a study on sender initiated contention based MAC protocols without reservation mechanisms in wireless ad-hoc networks.
The proceedings contain 111 papers. The topics discussed include: evolutionary multiobjective optimization and multiobjective fuzzy system design;chance discovery as value sensing by data based meta cognition;building...
ISBN:
(纸本)9781605580463
The proceedings contain 111 papers. The topics discussed include: evolutionary multiobjective optimization and multiobjective fuzzy system design;chance discovery as value sensing by data based meta cognition;building classification rules for case based classifier using fuzzy sets and formal concept analysis;intelligent hybrid system for patternrecognition and classification;hybrid approach using ant colony optimization and fuzzy logic to solve multi-criteria hybrid flow shop scheduling problem;improving performance of intrusion detection system by applying a new machine learning strategy;network security simulation and evaluation;extending web applications with a lightweight zero knowledge proof authentication;implementation of a neural-based navigation approach on indoor and outdoor mobile robots;a human-machine interface design for direct rehabilitation using a rehabilitation robot;and Persian on-line handwritten character recognition by RCE spatio-temporal neural network.
Constructive neural network algorithms provide optimal ways to determine the architecture of a multi layer perceptron network along with learning algorithms for determining appropriate weights for pattern classificati...
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ISBN:
(纸本)9788132204862
Constructive neural network algorithms provide optimal ways to determine the architecture of a multi layer perceptron network along with learning algorithms for determining appropriate weights for pattern classification problems. In this paper the possibility of developing a novel Constructive Neural Network architecture with improved adaptive learning strategy is proposed and analyzed. The new Multi category Tiling Constructive Neural Network architecture and the existing Tiling architecture are tested on machine learning datasets. The performance of the new learning strategy on Multi Category Tiling architecture was found to be comparatively better than when applied on the existing Tiling architecture.
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