Finding Protein Complexes via Fuzzy Learning Vector Quantization Algorithm

نویسندگان

  • Hamid Ravaee
  • Ali Masoudi-Nejad
  • Ali Moeini
چکیده

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Image Compression Based on a Novel Fuzzy Learning Vector Quantization Algorithm

We introduce a novel fuzzy learning vector quantization algorithm for image compression. The design procedure of this algorithm encompasses two basic issues. Firstly, a modified objective function of the fuzzy c-means algorithm is reformulated and then is minimized by means of an iterative gradient-descent procedure. Secondly, the training procedure is equipped with a systematic strategy to acc...

متن کامل

An axiomatic approach to soft learning vector quantization and clustering

This paper presents an axiomatic approach to soft learning vector quantization (LVQ) and clustering based on reformulation. The reformulation of the fuzzy c-means (FCM) algorithm provides the basis for reformulating entropy-constrained fuzzy clustering (ECFC) algorithms. This analysis indicates that minimization of admissible reformulation functions using gradient descent leads to a broad varie...

متن کامل

Prototype Based Classification Using Information Theoretic Learning

In this article we extend the (recently published) unsupervised information theoretic vector quantization approach based on the Cauchy–Schwarz-divergence for matching data and prototype densities to supervised learning and classification. In particular, first we generalize the unsupervised method to more general metrics instead of the Euclidean, as it was used in the original algorithm. Thereaf...

متن کامل

Fuzzy-Kernel Learning Vector Quantization

This paper presents an unsupervised fuzzy-kernel learning vector quantization algorithm called FKLVQ. FKLVQ is a batch type of clustering learning network by fusing the batch learning, fuzzy membership functions, and kernel-induced distance measures. We compare FKLVQ with the wellknown fuzzy LVQ and the recently proposed fuzzy-soft LVQ on some artificial and real data sets. Experimental results...

متن کامل

Fuzzy entropy-constrained competitive learning algorithm

A novel variable-rate vector quantizer (VQ) design algorithm using both fuzzy and competitive learning technique is presented. The algorithm enjoys better rate-distortion performance than that of other existing fuzzy clustering and competitive learning algorithms. In addition, the learning algorithm is less sensitive to the selection of initial reproduction vectors. Therefore, the algorithm can...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2017