In this paper several neural network classiication algorithms have been applied to a real-world data case of electron microscopy image classiication in which it was known a priori the existence of two diierentiated views of the same specimen. Using several labeled sets as a reference, the parameters and architecture of the classiier (both LVQ trained codebooks and BP trained neural-nets) were o...

Neuro-fuzzy approach have attracted considerable attention in the computational intelligence and segmentation algorithms have been increasingly in developed in improving the accuracy of medical diagnosis. Fuzzy set attempts to represent the human perception whereas neural network attempt to emulate the architecture and information representation scheme of human brain. In this paper a comparativ...

In image classification, there are no labeled training instances for some classes, which therefore called unseen classes or test classes. To classify these zero-shot learning (ZSL) was developed, typically attempts to learn a mapping from the (visual) feature space semantic in represented by list of semantically meaningful attributes. However, fact that this is learned without using affects per...

Input feature ranking and selection represent a necessary preprocessing stage in classification, especially when one is required to manage large quantities of data. We introduce a weighted LVQ algorithm, called Energy Relevance LVQ (ERLVQ), based on Onicescu’s informational energy [10]. ERLVQ is an incremental learning algorithm for supervised classification and feature ranking.

OBJECTIVE A self-organizing map (SOM) is a competitive artificial neural network with unsupervised learning. To increase the SOM learning effect, a fuzzy-soft learning vector quantization (FSLVQ) algorithm has been proposed in the literature, using fuzzy functions to approximate lateral neural interaction of the SOM. However, the computational performance of FSLVQ is still not good enough, espe...

سیستم حمل‌ونقل ریلی از تعامل مجموعه‌ای تجهیزات و عملیات تشکیل‌ شده است که توانایی ظرفیت یک در بار مسافر را تعیین می‌کند. بدین‌منظور، محاسبة پیش‌بینی نحوة تغییرات آن مهم شناخت آن‌ کمک شایانی به ارتقای سطح بهره‌برداری شبکة روش‌های گوناگونی برای وجود دارد با توجه نوع شبکه شیوة استفاده این روش‌ها، می‌توان آنها بهره گرفت. ظرفیت، توانمندی‌های سیستم‌های اطلاعات مکانی می‌شود تحت وب، وضعیت ظرفیتی عملیات...

We propose a new learning method, "Generalized Learning Vector Quantization (GLVQ)," in which reference vectors are updated based on the steepest descent method in order to minimize the cost function . The cost function is determined so that the obtained learning rule satisfies the convergence condition. We prove that Kohonen's rule as used in LVQ does not satisfy the convergence condition and ...

We compare the performance of ve algorithms for vector quan-tisation and clustering analysis: the Self-Organising Map (SOM) and Learning Vector Quantization (LVQ) algorithms of Kohonen, the Linde-Buzo-Gray (LBG) algorithm, the MultiLayer Perceptron (MLP) and the GMM/EM algorithm for Gaussian Mixture Models (GMM). We propose that the GMM/EM provides a better representation of the speech space an...