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This paper propose a novel fault diagnosis of bearings approach based on sparse representation. Three steps are conducted to classify the fault types. In the dictionary learning step, dictionary is learned using training set with known fault types; in the sparse coding step, testing samples with unknown fault types are represented through spares representation model with sub-dictionaries extracted...
To diagnose and classify the dysarthric speech, speech language pathologist (SLP) conducts a listening test. On the basis of the scores given by listeners the dysarthria is diagnosed and assessed. The above mentioned method is costly, time consuming and not very accurate. Unlike the traditional method, this research proposes an automatic diagnosis and assessment of dysarthria. The aim of this paper...
Mortality rate increases all over the world on a daily basis. The reason for this could be largely adduced to the increase in the number of patients with cardiovascular diseases. To worsen the case, many physicians have been known for misdiagnosis of patients reporting heart related ailment. In this paper, an intelligent system has been design which will help in effective diagnosis of the patient...
Testing and diagnosis of analog circuits are very important tasks at the quality assurance of integrated circuits and electronic devices. Faults detection and identification are realized using fault dictionary. The architecture of fault dictionary has an essential influence on time and efficiency of diagnosis at whole. An approach to the construction of fault dictionary as the neuromorphic classifier...
Objective: To study the artificial neural network in the diagnosis of the smear negative pulmonary tuberculosis. Methods: All original data was randomized into modeling sample and validating sample. The modeling sample was further randomized into training sample and testing sample. The training sample was used to screen out significant single parameters and to develop the diagnostic model of smear...
Epilepsy is a common chronic neurological disorder that is characterized by recurrent unprovoked seizures. About 50 million people worldwide have epilepsy at any one time. This paper presents an Intelligent Diagnostic System for Epilepsy using Artificial Neural Networks (ANNs) and Neuro-Fuzzy technique. In this approach the feed-forward neural network has been trained using Back propagation algorithm...
In this paper, a new classification method that is based on discrete wavelet transform (DWT) and adaptive neuro-fuzzy inference system (ANFIS) is proposed to classify power quality disturbances. First, the multiresolution signal analysis technique of DWT and Parseval's theorem are employed to extract discriminating features of the disturbance signal. Then, the proposed classifier system can identify...
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