Data mining is the upcoming research area to solve various problems and classification is one of main problem in the field of data mining. In this paper, we use two classification algorithms J48 (which is java implementation of C4. 5 algorithm) and multilayer perceptron alias MLP (which is a modification of the standard linear perceptron) of the Weka interface. It can be used for testing severa...

In this paper we present our teamwork main results in the area of the automatic speech recognition and understanding in Romanian language using hidden Markov models (HMM), artificial neural networks (multilayer perceptron, support vector machines, Kohonen networks) and hybrid models (fuzzy HMM, fuzzy multilayer perceptron, HMM/multilayer perceptron) for different small Romanian language corpora...

In this paper we propose and analyze a multilayer perceptron-like model with matrix inputs. We applied the proposed model to the financial time series prediction problem, compared it with the standard multilayer perceptron model, and got fairly good results.

In this paper, simulated annealing guided traingularized encryption using multilayer perceptron generated session key (SATMLP) has been proposed for secured wireless communication. Both sender and receiver station uses identical multilayer perceptron and depending on the final output of the both side multilayer perceptron, weights vector of hidden layer get tuned in both ends. After this tunnin...

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...

In this paper, a new Transform Domain implementation of the well known Multilayer Perceptron Neural Network is presented. With the Transform Domain implementation, the input of the Neural Network can be represented in a more compact manner and the elements of the input vector become uncorrelated. The new Transform Domain Multilayer Perceptron (TDMLP) Neural Network is applied for the problem of...

In this work we present a variational formulation for a multilayer perceptron neural network. With this formulation any learning task for the neural network is defined in terms of finding a function that is an extremal for some functional. Thus the multilayer perceptron provides a direct method for solving general variational problems. The application of this numerical method is investigated th...

How do we determine the mutational effects in exome sequencing data with little or no statistical evidence? Can protein structural information fill in the gap of not having enough statistical evidence? In this work, we answer the two questions with the goal towards determining pathogenic effects of rare variants in rare disease. We take the approach of determining the importance of point mutati...