Motivation: Polyproline type II stretches are rather rare among proteins, and, therefore, it is a very challenging task to try to find them computationally. In the present study our aim was to consider especially the preprocessing phase, which is important for any machine learning method. Preprocessing includes selection of relevant data from Protein Data Bank and investigation of learnability ...

Estimation of population covariance matrices from samples of multivariate data is important. (1) Estimation of principle components and eigenvalues. (2) Construction of linear discriminant functions. (3) Establishing independence and conditional independence. (4) Setting confidence intervals on linear functions. Suppose we observed p dimensional multivariate samples X1, X2, · · · , Xn i.i.d. wi...

in this paper, a state-of-the-art neuron mathematical model of neural tensor network (ntn) is proposed to rdf knowledge base completion problem. one of the difficulties with the parameter of the network is that representation of its neuron mathematical model is not possible. for this reason, a new representation of this network is suggested that solves this difficulty. in the representation, th...

Electroencephalogram (EEG) is an important clinical tool for diagnosing, monitoring, and managing neurological disorders related to epilepsy. Neural networks provide intriguing possibilities for the analysis of the EEG. In this paper we propose a neural network based system to detect epileptic activity. The system comprises of three main components: feature extraction, feature quantization and ...

This paper presents a study on classification of blasts in acute leukemia blood samples using artificial neural network. In acute leukemia there are two major forms that are acute myelogenous leukemia (AML) and acute lymphocytic leukemia (ALL). Six morphological features have been extracted from acute leukemia blood images and used as neural network inputs for the classification. Hybrid Multila...

The aim of the present work was to find the answer to the question: To what extent can the multilayer perceptron be applicable in the automatic vowel recognition process in any given fragments of a particular speaker? Initial research was carried out with the use of recordings of 3 adult people’s speech. Vowel recognition was performed with the application of multilayer perceptron. On the input...

Amultivariate change point control chart based on data depth (CPDP) is considered for detecting shifts in either the mean vector, the covariance matrix, or both of the process for Phase I. The proposed chart is preferable from a robustness point of view, has attractive detection performance and can be especially useful in Phase I analysis setting where there is limited information about the und...

this paper extends the sequential learning algorithm strategy of two different types of adaptive radial basis function-based (rbf) neural networks, i.e. growing and pruning radial basis function (gap-rbf) and minimal resource allocation network (mran) to cater for on-line identification of non-linear systems. the original sequential learning algorithm is based on the repetitive utilization of s...

This paper proposes an approach to construct a better Semantic Perceptron Net (SPN) used for topic spotting. To accomplish this task a learning paradigm call: neural network ensembling is used. Applying this technique to the original structure of Semantic Perceptron Net a new system called GA-SPN (Genetic Algorithm based Semantic Perceptron Net) was developed. The new system uses a neural netwo...