We present a new incremental radial basis function network suitable for classiication and regression problems. Center positions are continuously updated through soft competitive learning. The width of the radial basis functions is derived from the distance to topological neighbors. During the training the observed error is accumulated locally and used to determine where to insert the next unit....

We use a multifluid, spherically symmetric, MHD model with neutral atoms and pickup protons, with 1999 solar wind data at 1 AU as input, to calculate the magnetic field strength (B) profiles that would be observed at various points between 1 and 60 AU with a resolution of 1 day over an interval of 1 yr. These temporal profiles show radial evolution of the multiscale fluctuations in B near solar...

Training and application of prototype based learning approaches such as Learning Vector Quantization, Radial Basis Function networks, and Supervised Neural Gas require the use of distance metrics to measure the similarities between feature vectors as well as class prototypes. While the Euclidean distance is used in many cases, the highly correlated features within the hyperspectral representati...

In this paper, a face recognition algorithm using multi feature and Radial basis Function Network (RBFN) is proposed. The algorithm consists of three steps. In the first step, a coarse classification is performed using Fourier frequency spectrum feature, and only the first k gallery images with minimum Euclidean distance to the probe image are retained. In the second step, the Principal Compone...

We present a new algorithm for the construction of radial basis function (RBF) networks. The method uses accumulated error information to determine where to insert new units. The diameter of the localized units is chosen based on the mutual distances of the units. To have the distance information always available, it is held up-to-date by a Hebbian learning rule adapted from the "Neural Gas" al...

A general and rigorous method to deal with singularities at the origin of a polar coordinate system is presented. Its power derives from a clear distinction between the radial distance and the radial coordinate variable, which makes that all delta-functions and their derivatives are automatically generated, and insures that the Gauss theorem is correct for any distribution with a finite number ...

Atmospheric aerosols play a very important role in atmospheric processes and have a major influence on the global climate. In this paper, we report results of a molecular dynamics study on the unique properties of organic-coated water droplets. In particular, we find that, for particles preferring an inverted micelle structure, the lower chain-chain interaction, with increasing radial distance ...

Objective(s): The present study was conducted to examine whether the standardized uptake value (SUV) may be affected by the spatial position of a lesion in the radial direction on positron emission tomography (PET) images, obtained via two methods based on time-of-flight (TOF) reconstruction and point spread function (PSF). Methods: A cylinder phantom with the sphere (30mm diameter), located in...

In this paper, we examine the properties of radial distance which has been used as a tool to compare shape simple surfacic objects. We give rigorous definition and derive its theoretical properties, in particular under conditions it satisfies properties. show how computation can be implemented practice made faster by use an analytical formula Fast Fourier Transform. Finally, conduct experiments...

nonstationary channel equalisation problem Eng-Siong Chng y 1, Howard Yang z, Herbert Wiklickyz y Institute of Systems Science, National University of Singapore, Singapore 11957. Email : [email protected] z Brain Information Processing Group, Frontier Research Programme, RIKEN. 2-1 Hirosawa, Wako-shi, Saitama 351-01, JAPAN. Abstract| The computational requirement to implement the optimal Bayesi...