The MATLAB based simulation on simulink platform is presented for Single Phase Cascaded symmetric Multilevel Inverter for 5 levels. Theoretical study is done for the classification of multilevel inverter. And also the study is done for the classification of modulation scheme for multilevel inverter. Modulation scheme used for single phase symmetric multilevel inverter is fixed frequency multica...

The goal of this paper is to address the problem of evaluating the performance of a system running under unknown values for its stochastic parameters. A new approach called LAD for Simulation, based on simulation and classification software, is presented. It uses a number of simulations with very few replications and record the mean value of directly measurable quantities (called observables). ...

This paper addresses pattern classification in dynamical systems, where the underlying algorithms are formulated in the symbolic domain and the patterns are constructed from symbol strings as probabilistic finite state automata (PFSA) with (possibly) diverse algebraic structures. A combination of Dirichlet and multinomial distributions is used to model the uncertainties due to the (finite-lengt...

This paper discusses modelling methodology of the energy use of a certain amount of building stock at the city/regional/national level. In the methodology, building stock is divided into several stock categories and unit energy consumption for each category is quantified by performing simulations using prototypical building models as simulation input each representing a building stock category....

In this paper, a new comprehensive intelligent control strategy based on connectionist learning of robotic system uncertainties and wavelet network classification of unknown robot environments is proposed. The proposed wavelet neural network classifies characteristics of environments, determines the control parameters for compliance control and in coordination with basic learning compliance con...

Many kinds of uncertain factors may exist in the process of fault diagnosis and affect diagnostic results. Bayesian network is one of the most effective theoretical models for uncertain knowledge expression and reasoning. The method of naive Bayesian classification is used in this paper in fault diagnosis of a proton exchange membrane fuel cell (PEMFC) system. Based on the model of PEMFC, fault...

The electromyogram (EMG) signal contains lots of information about muscular changes related muscular disorder such as myopathy. In this paper, we present a new method for classification of EMG signals based on singular value decomposition. The EMG signal represent in the matrix form, features extracted from the singular value decomposition and singular value of EMG signal used as features for c...

In order to improve the recognition rate and accuracy of stored grain pests classification, saving classification time, a new recognition method based on the Gabor wavelet and sparse representation is proposed in this paper. In this paper, nine typical pests in the stored grain are regarded as the research object, Gabor energy features and morphological features are extracted, principal compone...

Correct classification of various kinds of scenes in sport videos is essential for higher-level content analysis such as event detection. The paper presents a novel technique for the classification of the typical scenes of baseball videos. The spatial color features are employed to detect pitch scene first. The temporal features derived from a shot are utilized to classify infield and outfield ...

A method is presented that enables automatic classification of medical diagnoses through their reports in natural language. The method is based on the nearest neighbor rule: classification of a new case by assigning to it the same codes as the most similar case in the archive. A simulation experiment showed that in 84% of the trials a suitable classification was contained within the first five ...