In this brief, a new neural network model called generalized adaptive resonance theory (GART) is introduced. GART is a hybrid model that comprises a modified Gaussian adaptive resonance theory (MGA) and the generalized regression neural network (GRNN). It is an enhanced version of the GRNN, which preserves the online learning properties of adaptive resonance theory (ART). A series of empirical ...

An adaptive neural feedback tracking control scheme is presented for a class of multi-input multi-output nonlinear minimum phase systems with uncertainties and external disturbances. Gaussian basis RBF neural networks are used to approximate the plant unknown nonlinearities, and a high-gain observer is used to estimate the states which can not be measured. The proposed controller can guarantee ...

In this paper, we introduce a new kernel function called polynomial radial basis function (PRBF) that could improve the classification accuracy of support vector machines (SVMs). The proposed kernel function combines both Gauss (RBF) and Polynomial (POLY) kernels and is stated in general form. It is shown that the proposed kernel converges faster than the Gauss and Polynomial kernels. The accur...

We establish a general oracle inequality for clipped approximate minimizers of regularized empirical risks and apply this inequality to support vector machine (SVM) type algorithms. We then show that for SVMs using Gaussian RBF kernels for classification this oracle inequality leads to learning rates that are faster than the ones established in [9]. Finally, we use our oracle inequality to show...

In this paper we consider the problem of approximating functions from noisy data. We propose an incremental supervised learning algorithm for RBF networks. Hidden gaussian nodes are added in an iterative manner during the training process. For each new node added, the activation function center and the output connection weight are settled according to an extended chained version of the Nadaraja...

Exact structure from motion is an ill-posed computation and therefore very sensitive to noise. In this work I describe how a qualitative shape representation, based on the sign of the Gaussian curvature, can be computed directly from motion disparities, without the computation of an exact depth map or the directions of surface normals. I show that humans can judge the curvature sense of three p...

work, applies a nonlinear transformation from the input space to the hidden space. The output layer Partial face images, e.g.1 eyes, nose, and ear supplies the response of the network to the activaimages are significant for face recognition. In this tion pattern. paper, we present a method for partial face extraction and recognition based on Radial Basis Function (RBF) networks. Focus has been ...

Verifikasi kualitas gambar pada aplikasi DiTenun sebelumnya dilakukan menggunakan algoritma Fast Four Transform (FFT) dan Principle Componen Analysis (PCA). Pada penelitian ini verifikasi Support Vector Machine (SVM) untuk dapat digunakan DiTenun. SVM membentuk model klasifikasi ke dalam kategori baik buruk. Algoritma yang adalah non-linear dengan kernel berbeda, yaitu gaussian rbf, polynomial,...

INTRODUCTION To assess changes in renal blood flow (RBF) in human and experimental sepsis, and to identify determinants of RBF. METHOD Using specific search terms we systematically interrogated two electronic reference libraries to identify experimental and human studies of sepsis and septic acute renal failure in which RBF was measured. In the retrieved studies, we assessed the influence of ...

Scheme identification system is required to improve the socio-economic status of marginalized people. The absence technological innovations creates more complications during online scheme identifications for development In order increases service availability people, a proposed. this, previous beneficiary data collected from Kerala state SC, women and Handicapped Persons cooperation are used. S...