Selective Learning for Multilayer Feedforward Neural Networks
نویسنده
چکیده
منابع مشابه
Using the Taylor expansion of multilayer feedforward neural networks
The Taylor series expansion of continuous functions has shown in many fields to be an extremely powerful tool to study the characteristics of such functions. This paper illustrates the power of the Taylor series expansion of multilayer feedforward neural networks. The paper shows how these expansions can be used to investigate positions of decision boundaries, to develop active learning strateg...
متن کاملAn ]Efficient Multilayer Quadratic Perceptron for Pattern Classification and Function Approximation
Abs t rac t : W e propose an architecture of a multilayer quadratic perceptron (MLQP) that combines advantages of multilayer perceptrons(MLPs) and higher-order feedforward neural networks. The features of MLQP are in its simple structure, practical number of adjustable connection weights and powerful learning ability. I n this paper, the architecture of MLQP is described, a backpropagation lear...
متن کاملA Selective Learning Method to Improve the Generalization of Multilayer Feedforward Neural Networks
Multilayer feedforward neural networks with backpropagation algorithm have been used successfully in many applications. However, the level of generalization is heavily dependent on the quality of the training data. That is, some of the training patterns can be redundant or irrelevant. It has been shown that with careful dynamic selection of training patterns, better generalization performance m...
متن کاملImage Segmentation Using a RBF Approach of Neural Network
Radial Basis function Neural Networks forms a class of neural networks which is much more advantageous then other methods of neural networks such as faster learning, easy networks & structures & better approximations & classifications. The system consist of a multilayer perceptron (MLP)-like network that performs image segmentation by RBF technique of the input image using labels automatically ...
متن کاملApplication of Sfg in Learning Algorithms of Neural Networks
The paper presents application of signal ow graphs SFG and adjoint ow graphs AFG in determination of gradient vector for feedforward neural networks The presented approach is universal and applicable in the same form irrespective of the particular structure of the network The applicability of the method has been shown on the example of di erent types of neural networks multilayer perceptron sig...
متن کامل