Image segmentation plays an important role in medical image processing. Fuzzy c-means (FCM) clustering is one of the popular clustering algorithms for medical image segmentation. However, FCM has the problems of depending on initial clustering centers, falling into local optimal solution easily, and sensitivity to noise disturbance. To solve these problems, this paper proposes a hybrid artifici...

سلج 36 روم 07 / 02 / 94 و يس و دصكي نيمشش يشهوژپ ياروش هسلج تروص 1 . هسلج ليكشت تعاس و خيرات ،زور : زور هبنشود خيرات هب 07 / 02 / 94 هسلج نامز تدم 2 زا تعاس 14 تياغل 16 2 . يدعب هسلج خيرات : 28 / 02 / 94 3 . هسلج ليكشت لحم : يشهوژپ تنواعم رتفد 4 . هسلج رد هدننك تكرش ءاضعا : 1 ناراجشا يلع رتكد 2 رتكد يمولظم يلع رف 3 رفدنمجرا سابع رتكد 4 يرفعج دمحم رتكد يدنره 5 يضاق ديعس رتكد يبرغم ...

* لوئسم هدنسيون : فيرـش نابايخ ،ناهفصا يوـك ،يـفقاو نب ،يناطلس نسحم ديهش حرف تسب كلاپ ،شخب 10 / 8 نفلت : 3168058 0913 email: [email protected] فده و هنيمز : ميزنآ نيرتمهم زا زانژيسكا ولكيس ميزنآ نيدنلاگاتسورپ زتنس ريسم ياه ا شياديپ و اه ندب رد باهتل تسا ناسنا . هزات رد رثا تاقيقحت نيرت ت رخ ي زانژيسكا ولكيس ميزنا زا يب 2 لولس رب هدش هديد ناسنا زغم يبصع ياه ب تسا ه يروط...

To overcome the noise sensitiveness of conventional fuzzy c-means (FCM) clustering algorithm, a novel extended FCM algorithm for image segmentation is presented in this paper. The algorithm is developed by modifying the objective function of the standard FCM algorithm with a penalty term that takes into account the influence of the neighboring pixels on the centre pixels. The penalty term acts ...

مداخل يعسوت رامعم ميمصت " ةجاحلا بسح ةددعتم طئاسو " ABSTRACT in this paper we develop a Vhdlbased scalable architecture of a multimedia on demand server model. Te three server subsystems are:the control subsystem, the communication subsystem and the storage subsystem are modeled. The communication subsystem is designed as an interconnection network with meshed-pipe structure and delivers packe...

PCA and ICA are two powerful techniques for feature extraction. In addition, fuzzy c-means clustering (FCM) is among considerable techniques for data reduction. In other words, the aim of using FCM is to decrease the number of segments by grouping similar segments in training data. In this work, an improved version of PCA and ICA is proposed for feature extraction to classify the ischemic beats...

Fuzzy c-means (FCM) has been considered as an effective algorithm for image segmentation. However, it still suffers from two problems: one is insufficient robustness to image noise, and the other is the Euclidean distance in FCM, which is sensitive to outliers. In this paper, we propose two new algorithms, generalized FCM (GFCM) and hierarchical FCM (HFCM), to solve these two problems. Traditio...

1 يوجشناد سانشراک ی ،هیذغت مولع دشرا ،نارهت یکشزپ مولع هاگشناد ،یسانش میژر و هیذغت هدکشناد ناریا 2 لوئسم هدنسیون : هورگ رایداتسا هیذغت هعماج ،ناریا ،نارهت یکشزپ مولع هاگشناد ،یسانش میژر و هیذغت هدکشناد ، یکینورتکلا تسپ : [email protected] 3 داتسا هورگ هیذغت هعماج هدکشناد، هیذغت میژرو هاگشناد،ینامرد مولع یکشزپ ،نارهت ناریا 4 يارتکد تملاس تاقیقحت یلم وتیتسنا ،ناهفصا یتشادهب ت...

The traditional fuzzy C-means(FCM) algorithm is an optimization algorithm based on gradient descending, it is sensitive to the initial condition and liable to be trapped in a local optimum. Search space smoothing allows a local search heuristics to escape from a poor, local optimum. In this paper, an improved FCM algorithm based on search space smoothing is proposed. By designing a proper smoot...

Fuzzy Cognitive Maps (FCMs) have successfully been applied in numerous domains to show relations between essential components. In some FCM, there are more nodes, which related to each other and more nodes means more complex in system behaviors and analysis. In this paper, a novel learning method used to construct FCMs based on historical data and by using data mining and DEMATEL method, a new m...