Errata to "Model Transitions in Descending FLVQ"
نویسندگان
چکیده
[1] K. J. Hunt, R. Hass, and R. Murray-Smith, “Extending the functional equivalence of radial basis function networks and fuzzy inference systems,” IEEE Trans. Neural Networks, vol. 7, pp. 776–781, May 1996. [2] J.-S. R. Jang, C.-T. Sun, and E. Mizutani, Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence, MATLAB Curriculum Series. Upper Saddle River, NJ: Prentice-Hall, 1997. [3] D. F. Specht, “A generalized regression neural network,” IEEE Trans. Neural Networks, vol. 2, pp. 568–576, Nov. 1991. Errata to “Model Transitions in Descending FLVQ”
منابع مشابه
Model transitions in descending FLVQ
Fuzzy learning vector quantization (FLVQ), also known as the fuzzy Kohonen clustering network, was developed to improve performance and usability of on-line hard-competitive Kohnen's vector quantization and soft-competitive self organizing map (SOM) algorithms. The FLVQ effectiveness seems to depend on the range of change of the weighting exponent m(t). In the first part of this work, extreme m...
متن کاملA Survey of Fuzzy Clustering Algorithms for Pattern Recognition—Part II
In Part I of this paper [1], an equivalence between the concepts of fuzzy clustering and soft competitive learning in clustering algorithms is proposed on the basis of the existing literature. Moreover, a set of functional attributes is selected for use as dictionary entries in the comparison of clustering algorithms. In this paper, five clustering algorithms taken from the literature are revie...
متن کاملSoft-to-hard Model Transition in Clustering: a Review
Clustering analysis often employs unsupervised learning techniques originally developed for vector quantization. In this framework, a frequent goal of clustering systems is to minimize the quantization error, which is aaected by many local minima. To avoid connnement of reference vectors to local minima of the quantization error and to avoid formation of dead units, hard c-means clustering algo...
متن کاملSeismic Events Discrimination Using a New FLVQ Clustering Model
In this paper, the LVQ (Learning Vector Quantization) model and its variants are regarded as the clustering tools to discriminate the natural seismic events (earthquakes) from the artificial ones (nuclear explosions). The study is based on the six spectral features of the P-wave spectra computed from the short period teleseismic recordings. The conventional LVQ proposed by Kohenen [2] and also ...
متن کاملGCMC Glauber dynamics study for structural transitions in YBCOx (0<x<1), HTc system
We have chosen an Ising ASYNNNI (ASYmmetric Next Nearest Neighbor Interaction) model under a grand canonical regime to investigate structural phase transition from a high symmetric tetragonal (Tet) to a low symmetric orthorhombic in YBa2Cu3O6+x , 0<x<1, HTc system. Ordering process for absorbed oxygens from an external gas bath into the basal plane of the layered system is studied by Monte C...
متن کاملذخیره 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 ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- IEEE Trans. Neural Networks
دوره 9 شماره
صفحات -
تاریخ انتشار 1998