دانلود رایگان مجموعه مقالات علمی اشپرینگر در زمینه منطق فازی — بخش سی و چهارم

منطق فازی (Fuzzy Logic) اولین بار در پی تنظیم نظریه مجموعه‌های فازی به وسیله پروفسور لطفی زاده (۱۹۶۵ میلادی) در صحنه محاسبات نو ظاهر شد. در واقع منطق فازی از منطق ارزش‌های «صفر و یک» نرم‌افزارهای کلاسیک فراتر رفته و درگاهی جدید برای دنیای علوم نرم‌افزاری و رایانه‌ها می‌گشاید، زیرا فضای شناور و نامحدود بین اعداد صفر و یک را نیز در منطق و استدلال‌های خود به کار می‌گیرد. در ادامه مقالات علمی انتشارات بین المللی اشپرینگر (Springer) در زمینه منطق فازی (Fuzzy Logic) برای دانلود آمده است. می توانید برای دانلود هر یک از مقالات از سرور دانلود متلب سایت، بر روی لینک دانلود هر یک از آن ها، کلیک کنید.

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دانلود رایگان مجموعه مقالات علمی اشپرینگر در زمینه منطق فازی — فهرست اصلی

عنوان اصلی مقاله On the property of T-distributivity
نوع مقاله مقاله ژورنال
نویسندگان Mücahide Nesibe Kesicioğlu
چکیده / توضیح In this paper, we introduce the notion of T-distributivity for any t-norm on a bounded lattice. We determine a relation between the t-norms T and , where is a T-distributive t-norm. Also, for an arbitrary t-norm T, we give a necessary and sufficient condition for to be T-distributive and for T to be -distributive. Moreover, we investigate the relation between the T-distributivity and the concepts of the T-partial order, the divisibility of t-norms. We also determine that the T-distributivity is preserved under the isomorphism. Finally, we construct a family of t-norms which are not distributive over each other with the help of incomparable elements in a bounded lattice.
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عنوان اصلی مقاله Existence and exponential stability of an equilibrium point for fuzzy BAM neural networks with time-varying delays in leakage terms on time scales
نوع مقاله مقاله ژورنال
نویسندگان Yongkun Li, Li Yang, Lijie Sun
چکیده / توضیح In this paper, by using a fixed point theorem and differential inequality techniques, we consider the existence and global exponential stability of an equilibrium point for a class of fuzzy bidirectional associative memory neural networks with time-varying delays in leakage terms on time scales. We also present a numerical example to show the feasibility of obtained results. The results of this paper are completely new and complementary to the previously known results.
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عنوان اصلی مقاله Convergence analysis of algorithms for memristive oscillator system
نوع مقاله مقاله ژورنال
نویسندگان Ailong Wu, Chao-Jin Fu
چکیده / توضیح Memristive oscillator systems are common models for many problems in physics, engineering, and systems biology. This paper presents a convergence analysis of two types of algorithms for solving a fourth-order memristive oscillator system. For the first algorithm, a parallel algorithm, a limiting state of the iterate sequence generated by a Jacobi iterative scheme and the Euler polygonal method, is a solution of the system under some weaker conditions. With the second algorithm, a partial difference method, which is based on the partial difference concept and exponential convergence, is also presented. The proposed algorithms in this paper can be applied to general nonlinear hybrid systems.
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عنوان اصلی مقاله FPGA based wireless sensor node with customizable event-driven architecture
نوع مقاله مقاله ژورنال
نویسندگان Junsong Liao, Brajendra K Singh, Mohammed AS Khalid, Kemal E Tepe
چکیده / توضیح This article presents the design and implementation of modular customizable event-driven architecture with parallel execution capability for the first time with wireless sensor nodes using stand alone FPGA. This customizable event-driven architecture is based on modular generic event dispatchers and autonomous event handlers, which will help WSN application developers to quickly develop their applications by adding the required number of event dispatchers and event handlers as per the need of a WSN application. This architecture can handle multiple events in parallel, including high priority ones. Additionally, it provides non-preemptive operation which removes the timing uncertainty and overhead involved with interrupt-driven processor-based sensor node implementation, which is required in real-time wireless sensor networks (WSNs). Thus, higher computation power of FPGAs combined with the non-preemptive modular event-driven architecture with parallel execution capability enables a variety of new WSN applications and facilitates rapid prototyping of WSN applications. In this article, the performance of FPGA-based sensor device is compared with general purpose processor-based implementations of sensor devices. Results show that our FPGA-based implementation provides significant improvement in system efficiency measured in terms of clock cycle counts required for typical sensor network tasks such as packet transmission, relay and reception.
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عنوان اصلی مقاله Music content authentication based on beat segmentation and fuzzy classification
نوع مقاله مقاله ژورنال
نویسندگان Wei Li, Xiu Zhang, Zhurong Wang
چکیده / توضیح Digital audio has been ubiquitous over the past decade. Since it can be easily modified by editing tools, there has been a strong need to protect its content for secure multimedia applications. Previous audio authentication algorithms are mainly focused on either human speech or general audio with music as part of the test data, while special research on music authentication has been somewhat neglected. In this article, we propose a novel algorithm to protect the integrity and authenticity of music signals. Its main contributions include the following: (1) Music is segmented into beat-based frames, which not only endows the authentication units with more semantic meaning but also perfectly resolves the challenging synchronization problem. (2) Robust hashes are generated from chroma-based mid-level audio feature which can appropriately characterize the music content and integrated with an encryption procedure to ensure the security against malicious block-wise vector quantization attack. (3) Fuzzy logic is adopted to make the authentication decision in the light of three measures defined on bit errors, coinciding with the inherent blurred nature of authentication. The experiments exhibit good discriminative ability between admissible and malicious operations.
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عنوان اصلی مقاله Color image segmentation using multi-level thresholding approach and data fusion techniques: application in the breast cancer cells images
نوع مقاله مقاله ژورنال
نویسندگان Rafika Harrabi, Ezzedine Ben Braiek
چکیده / توضیح In this article, we present a new color image segmentation method, based on multilevel thresholding and data fusion techniques which aim at combining different data sources associated to the same color image in order to increase the information quality and to get a more reliable and accurate segmentation result. The proposed segmentation approach is conceptually different and explores a new strategy. In fact, instead of considering only one image for each application, our technique consists in combining many realizations of the same image, together, in order to increase the information quality and to get an optimal segmented image. For segmentation, we proceed in two steps. In the first step, we begin by identifying the most significant peaks of the histogram. For this purpose, an optimal multi-level thresholding is used based on the two-stage Otsu optimization approach. In the second step, the evidence theory is employed to merge several images represented in different color spaces, in order to get a final reliable and accurate segmentation result. The notion of mass functions, in the Dempster-Shafer (DS) evidence theory, is linked to the Gaussian distribution, and the final segmentation is achieved, on an input image, expressed in different color spaces, by using the DS combination rule and decision. The algorithm is demonstrated through the segmentation of medical color images. The classification accuracy of the proposed method is evaluated and a comparative study versus existing techniques is presented. The experiments were conducted on an extensive set of color images. Satisfactory segmentation results have been obtained showing the effectiveness and superiority of the proposed method.
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عنوان اصلی مقاله Robust fuzzy scheme for Gaussian denoising of 3D color video
نوع مقاله مقاله ژورنال
نویسندگان Alberto Jorge Rosales-Silva, Francisco Javier Gallegos-Funes, Ivonne Bazan Trujillo, Alfredo Ramírez García
چکیده / توضیح We propose a three-dimensional Gaussian denoising scheme for application to color video frames. The time is selected as a third dimension. The algorithm is developed using fuzzy rules and directional techniques. A fuzzy parameter is used for characterization of the difference among pixels, based on gradients and angle of deviations, as well as for motion detection and noise estimation. By using only two frames of a video sequence, it is possible to efficiently decrease Gaussian noise. This filter uses a noise estimator that is spatio-temporally adapted in a local manner, in a novel way using techniques mentioned herein, and proposing a fuzzy methodology that enhances capabilities in noise suppression when compared to other methods employed. We provide simulation results that show the effectiveness of the novel color video denoising algorithm.
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عنوان اصلی مقاله Magnitude-phase of the dual-tree quaternionic wavelet transform for multispectral satellite image denoising
نوع مقاله مقاله ژورنال
نویسندگان Mohammed Kadiri, Mohamed Djebbouri, Philippe Carré
چکیده / توضیح In this paper, we study the potential of the quaternionic wavelet transform for the analysis and processing of multispectral images with strong structural information. This new representation gives a very good division of the coefficients in terms of magnitude and three-phase angles and generalizes better the concept of analytic signal to image. Furthermore, it retains the property of shift invariant and directivity. We show an application of this transform in satellite image denoising. The proposed approach relies on the adaptation of thresholding procedures based on the dependency between magnitude quaternionic coefficients in local neighborhoods and phase regularization. In addition a non-marginal aspect of multispectral representation is introduced. Thanks to coherent analysis provided by the quaternionic wavelet transformation, the results obtained indicate the potential of this multispectral representation with magnitude thresholding and phase smoothing in noise reduction and edge preservation compared with classical wavelet thresholding methods that do not use phase or multiband information.
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عنوان اصلی مقاله Review of vision-based steel surface inspection systems
نوع مقاله مقاله ژورنال
نویسندگان Nirbhar Neogi, Dusmanta K Mohanta, Pranab K Dutta
چکیده / توضیح Steel is the material of choice for a large number and very diverse industrial applications. Surface qualities along with other properties are the most important quality parameters, particularly for flat-rolled steel products. Traditional manual surface inspection procedures are awfully inadequate to ensure guaranteed quality-free surface. To ensure stringent requirements of customers, automated vision-based steel surface inspection techniques have been found to be very effective and popular during the last two decades. Considering its importance, this paper attempts to make the first formal review of state-of-art of vision-based defect detection and classification of steel surfaces as they are produced from steel mills. It is observed that majority of research work has been undertaken for cold steel strip surfaces which is most sensitive to customers' requirements. Work on surface defect detection of hot strips and bars/rods has also shown signs of increase during the last 10 years. The review covers overall aspects of automatic steel surface defect detection and classification systems using vision-based techniques. Attentions have also been drawn to reported success rates along with issues related to real-time operational aspects.
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عنوان اصلی مقاله Retina identification based on the pattern of blood vessels using fuzzy logic
نوع مقاله مقاله ژورنال
نویسندگان Wafa Barkhoda, Fardin Akhlaqian, Mehran Deljavan Amiri, Mohammad Sadeq Nouroozzadeh
چکیده / توضیح This article proposed a novel human identification method based on retinal images. The proposed system composed of two main parts, feature extraction component and decision-making component. In feature extraction component, first blood vessels extracted and then they have been thinned by a morphological algorithm. Then, two feature vectors are constructed for each image, by utilizing angular and radial partitioning. In previous studies, Manhattan distance has been used as similarity measure between images. In this article, a fuzzy system with Manhattan distances of two feature vectors as input and similarity measure as output has been added to decision-making component. Simulations show that this system is about 99.75% accurate which make it superior to a great extent versus previous studies. In addition to high accuracy rate, rotation invariance and low computational overhead are other advantages of the proposed systems that make it ideal for real-time systems.
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