Testing the number of parameters of multidimensional MLP
نویسنده
چکیده
This work concerns testing the number of parameters in one hidden layer multilayer perceptron (MLP). For this purpose we assume that we have identifiable models, up to a finite group of transformations on the weights, this is for example the case when the number of hidden units is know. In this framework, we show that we get a simple asymptotic distribution, if we use the logarithm of the determinant of the empirical error covariance matrix as cost function.
منابع مشابه
Efficient estimation of multidimensional regression model using multilayer perceptrons
This work concerns the estimation of multidimensional nonlinear regression models using multilayer perceptrons (MLPs). The main problem with such models is that we need to know the covariance matrix of the noise to get an optimal estimator. However, we show in this paper that if we choose as the cost function the logarithm of the determinant of the empirical error covariance matrix, then we get...
متن کاملDetermination of Lateral load Capacity of Steel Shear Walls Based on Artificial Neural Network Models
In this paper, load-carrying capacity in steel shear wall (SSW) was estimated using artificial neural networks (ANNs). The SSW parameters including load-carrying capacity (as ANN’s target), plate thickness, thickness of stiffener, diagonal stiffener distance, horizontal stiffener distance and gravity load (as ANN’s inputs) are used in this paper to train the ANNs. 144 samples data of each of th...
متن کاملInvestigating the Factors Affecting Multidimensional Poverty Using Linear Mixed Beta Regression Model
Multidimensional poverty is a complex issue that is affected by various factors. Therefore, accurate knowledge and its comprehensive definition are great important. The aim of this study was to investigate the effect of economic, social and institutional factors on multidimensional poverty based on a comprehensive measurement framework and using the beta linear mixed regression model, which is ...
متن کاملNeural Network Performance Analysis for Real Time Hand Gesture Tracking Based on Hu Moment and Hybrid Features
This paper presents a comparison study between the multilayer perceptron (MLP) and radial basis function (RBF) neural networks with supervised learning and back propagation algorithm to track hand gestures. Both networks have two output classes which are hand and face. Skin is detected by a regional based algorithm in the image, and then networks are applied on video sequences frame by frame in...
متن کاملTesting Multidimensional and Hierarchical Model of School Motivation Questionnaire
Abstract Objective: One of the theories that motivation into a multi-objective model considers, Mayer's theory of personal investment. This theory is a useful framework for evaluating multi-dimensional and hierarchical nature of goal provides the motivation. The aim of this study is to investigate a multi-dimensional and hierarchical structure of achievement goal orientation. Methods: The popul...
متن کامل