Estimating the Number of Components in a Mixture of Multilayer Perceptrons

Asymptotic properties of mixture-of-experts models

Abstract. The statistical properties of the likelihood ratio test statistic (LRTS) for mixture-of-expert models are addressed in this paper. This question is essential when estimating the number of experts in the model. Our purpose is to extend the existing results for mixtures (Liu and Shao, 2003) and mixtures of multilayer perceptrons (Olteanu and Rynkiewicz, 2008). In this paper we study a s...

Steganalysis of embedding in difference of image pixel pairs by neural network

In this paper a steganalysis method is proposed for pixel value differencing method. This steganographic method, which has been immune against conventional attacks, performs the embedding in the difference of the values of pixel pairs. Therefore, the histogram of the differences of an embedded image is di_erent as compared with a cover image. A number of characteristics are identified in the di...

Local linear perceptrons for classification

A structure composed of local linear perceptrons for approximating global class discriminants is investigated. Such local linear models may be combined in a cooperative or competitive way. In the cooperative model, a weighted sum of the outputs of the local perceptrons is computed where the weight is a function of the distance between the input and the position of the local perceptron. In the c...

MAP decomposition of a mixture of AR signal using multilayer perceptrons

Determination of the number of components in finite mixture distribution with Skew-t-Normal components

Abstract One of the main goal in the mixture distributions is to determine the number of components. There are different methods for determination the number of components, for example, Greedy-EM algorithm which is based on adding a new component to the model until satisfied the best number of components. The second method is based on maximum entropy and finally the third method is based on non...