neural networks are applicable in identification systems from input-output data. in this report, we analyze thehammerstein-wiener models and identify them. thehammerstein-wiener systems are the simplest type of block orientednonlinear systems where the linear dynamic block issandwiched in between two static nonlinear blocks, whichappear in many engineering applications; the aim of nonlinearsyst...

Recently, shape-based matching and retrieval of 3D polygonal models has become one of the most fundamental problems in computer vision. Dealing with families of objects instead of a single one may impose further challenges on regular geometric algorithms. In this paper we focus on the classification of 3D objects based on their geodesic distance & path calculated on a mesh using an iterative al...

In the k-nearest neighbor (KNN) classifier, nearest neighbors involve only labeled data. That makes it inappropriate for the data set that includes very few labeled data. In this paper, we aim to solve the classification problem by applying transduction to the KNN algorithm. We consider two groups of nearest neighbors for each data point — one from labeled data, and the other from unlabeled dat...

This study aimed to predict the 1 2 year future time of financial failure 86 manufacturing companies that are operating in Borsa İstanbul. The data comprised 2010-2012 period, and it depends on 8 quantitative variables. Beside 6 variables come from non statements. In study, Artificial Neural Network (NN), Classification Regression Trees (CART), Support Vector Machine (SVM) k-Nearest Neighbors (...

it is necessary to use empirical models for estimating of instantaneous peak discharge because of deficit of gauging stations in the country. hence, at present study, two models including artificial neural networks and nonlinear multivariate regression were used to predict peak discharge in taleghan watershed. maximum daily mean discharge and corresponding daily rainfall, one day antecedent and...

AC Accuracy ADL Activities of daily living AF Average F-measure CNN Convolutional neural network CPU Central processing unit DBN Deep belief network DT Decision tree HA Hand Gesture HAR Human activity recognition KNN K-nearest neighbors LSTM Longand short-term memory MV Means and variance NB Naive Bayes NF Normalized F-measure OAR Opportunity activity recognition RAM Random access memory ReLU R...