The main focus of this study is on the modeling of the warranty claims and evaluating the warranty expenses. The cost of each warranty claim depends on the repair time associated with the claim. Alternating renewal pr...
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The main focus of this study is on the modeling of the warranty claims and evaluating the warranty expenses. The cost of each warranty claim depends on the repair time associated with the claim. Alternating renewal process is used to model the operating and repair times. The warranty costs over the warranty period under renewing free replacement policy are evaluated. Also, the expected warranty expenses over the life cycle of the product are studied. Numerical examples illustrate the ideas.
Image inpainting is an interpolation which guesses and fills in an imformation-losing portion according to its surroundings. Image inpainting belongs to the category of image restoration and reconstruction. The Total ...
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ISBN:
(纸本)0780384075
Image inpainting is an interpolation which guesses and fills in an imformation-losing portion according to its surroundings. Image inpainting belongs to the category of image restoration and reconstruction. The Total Variation model for image inpainting is an effective approach, however it fails to process the images damaged by a big noise and choosing its regular parameters is also difficult. We have made some improvements on it which can simultaneously denoise and preserve edges effectively filling in the missing area. This has been indicated theoretically and experimentally.
In this paper, the problem of inputs decoupled observer design for discrete-time descriptor systems with unknown inputs was considered. When the non-regular discrete-time descriptor systems were impulsively controllab...
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ISBN:
(纸本)0780388739
In this paper, the problem of inputs decoupled observer design for discrete-time descriptor systems with unknown inputs was considered. When the non-regular discrete-time descriptor systems were impulsively controllable, under the nonsingular transformation, equivalent discrete-time standard state space systems were derived by regarding the partial state as unknown input. The sufficient conditions for the existence of the observer and simple method to design the observer are given, and the state and unknown inputs of the discrete-time descriptor systems are asymptotically estimated by the state of observer and output of discrete-time descriptor systems.
To debluring edge after image magnifying an edge sharpness preserving image magnification simultaneously denoising well is put forword which follows the idea of the anisotropic diffusion of noise removal having review...
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ISBN:
(纸本)0780384075
To debluring edge after image magnifying an edge sharpness preserving image magnification simultaneously denoising well is put forword which follows the idea of the anisotropic diffusion of noise removal having reviewed the characters of typical *** experiments have verified the effectivity of our algorithm in this thesis.
A central problem in machine learning is identifying a representative set of features from which we will construct a classification model for a particular task. This paper addresses the problem of feature selection fo...
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ISBN:
(纸本)0780384032
A central problem in machine learning is identifying a representative set of features from which we will construct a classification model for a particular task. This paper addresses the problem of feature selection for machine learning through a correlation and MSVM (Modified Support Vector Machines) based approach. The central hypothesis is that a good feature set contains features that are highly correlated with the class, yet uncorrelated with each other. So we introduce the CMFS (Correlation and MSVM-based Feature Selection). First, CMFS ranks the features using MSVM according to their correlation with the class. Secondly, CMFS uses a forward selection search with correlation-based method to form feature subset. A feature can be added to the feature set or not decided by the class separability of the feature and the correlation with the already chosen features. Experiments on artificial and natural datasets show that, compared with other algorithms, CMFS typically eliminates well much more features with less time and higher accuracy.
A crucial prerequisite to externalized adaptation is an understanding of how components are interconnected, or more particularly how and why they depend on one another. Such dependencies can be used to provide an arch...
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ISBN:
(纸本)0769521959
A crucial prerequisite to externalized adaptation is an understanding of how components are interconnected, or more particularly how and why they depend on one another. Such dependencies can be used to provide an architectural model, which provides a reference point for externalized adaptation. In this paper, it is described how dependencies are used as a basis to systems' self-understanding and subsequent architectural reconfigurations. The approach is based on the combination of: instrumentation services, a dependency meta-model and a system controller. In particular, the latter uses self-healing repair rules (or conflict resolution strategies), based on an Extensible Beliefs, Desires and Intention (EBDI) model, to reflect reconfiguration changes back to a target application under examination.
Many lock-free data structures in the literature exploit techniques that are possible only because state-of-the-art 64-bit processors are still running 32-bit operating systems and applications. As software catches up...
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ISBN:
(纸本)9781581138023
Many lock-free data structures in the literature exploit techniques that are possible only because state-of-the-art 64-bit processors are still running 32-bit operating systems and applications. As software catches up to hardware, "64-bit-clean" lock-free data structures, which cannot use such techniques, are needed. We present several 64-bit-clean lock-free implementations: load-linked/store-conditional variables of arbitrary size, a FIFO queue, and a freelist. In addition to being portable to 64-bit software, our implementations also improve on previous ones in that they are space-adaptive and do not require knowledge of the number of threads that will access them.
The robust stabilization via state feedback for a class discrete-time singular systems with norm-bounded parameter uncertainties is discussed. Under a series of equivalent transformation, the equivalence between this ...
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The robust stabilization via state feedback for a class discrete-time singular systems with norm-bounded parameter uncertainties is discussed. Under a series of equivalent transformation, the equivalence between this problem and the robust stabilization via state feedback for uncertain standard state-space discrete-time linear systems with time-delays is obtained. In terms of LMI, a necessary and sufficient condition that there exists a robust state feedback stabilizing controller for all admissible uncertainties is given, the design method of the memoryless state feedback controller and a controller is also given.
Support Vector Machines (SVM) decomposition methods were proposed to solve high dimensional and/or large data classification problems. Two major decomposition algorithms: Karush-kuhn-Tucker (KKT) condition based algor...
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ISBN:
(纸本)0780384636
Support Vector Machines (SVM) decomposition methods were proposed to solve high dimensional and/or large data classification problems. Two major decomposition algorithms: Karush-kuhn-Tucker (KKT) condition based algorithm, and 'Joachims' decomposition algorithm are popularly adopted. In this paper, both these two decomposition methods are analyzed and applied into face recognition with three basic mapping kernels. Numerical results showed that: a) Face recognition with SVM performs better accuracy than other existed methods;b) The decomposition methods can perform face recognition efficiently;c) Joachims decomposition method has better accuracy than that of decomposition algorithm based on KKT condition;d) Linear kernel can provide much higher recognition accuracy than polynomial and slightly better accuracy then Gaussian radial based function (RBF) kernel;Also due to the fact that the linear kernel method is much simpler than others, it is most suitable for face recognition.
In this paper, a new family of Multi-band (M-band) wavelet with a parameter is proposed and applied to image coding, by which an image can be decomposed into M*M subbands. When the parameter varies from 0 to 2π, acco...
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ISBN:
(纸本)0780387481
In this paper, a new family of Multi-band (M-band) wavelet with a parameter is proposed and applied to image coding, by which an image can be decomposed into M*M subbands. When the parameter varies from 0 to 2π, according to the magnitude of the coefficients, each subband can be adaptively classified as significant subband and insignificant subband by a significance benchmark. For significant subband, the subband is further decomposed into blocks by quad-tree algorithm (QTP) and then coded. Otherwise, the subbands will be omitted. Experimental results show that for images with heavy textures, our method need less computational cost but has better capability than those based on 2-band wavelet. It also provides an encouraging promise to ROI coding.
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