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This paper presents the usage of Extreme Learning Machines for cancer microarray gene expression data. Extreme Learning Machines overcomes the problems of overfitting, local minima and improper training rate that are most common in traditional algorithms. We have evaluated the binary classification performance of Extreme Learning Machines on five bench marked datasets of cancer microarray gene expression...
Alzheimer's disease (AD) is the most common progressive neurodegenerative disorder. Therefore, early detection and evaluation of prognosis of AD is an important issue in contemporary brain research. Magnetic Resonance Imaging (MRI) provides valuable diagnostic information about AD. In this work, brain tissue is extracted using phase-based level set method. Structure tensor analysis is used to visualize...
Spirometric pulmonary function test is a wellestablished test in clinical medicine for the assessment of respiratory diseases. It measures the volume of air inhaled or exhaled as a function of time during forced breathing maneuvers and generates large data set. However, spirometric investigation is often prone to incomplete data sets due to inability of the children and patient to perform this test...
Electroencephalographms (EEGs) are records of brain electrical activity. It is an indispensable tool for diagnosing neurological diseases, such as epilepsy. Wavelet transform (WT) is an effective tool for analysis of non-stationary signal, such as EEGs. Wavelet analysis is used to decompose the EEG into delta, theta, alpha, beta, and gamma sub-bands. Lyapunov exponent is used to quantify the nonlinear...
In recent years, the security has become a critical part of any organizational information systems. The intrusion detection system is an effective approach to deal with the problems of networks using various neural network classifiers. In this paper, the performance of intrusion detection with various neural network classifiers is compared. In the proposed research the three types of classifiers used...
In recent times, analysis of transceiver RF front-end analog impairments and their compensation using digital signal processing techniques have drawn increasing interest. Analysis and calibration of frequency dependent and frequency independent IQ imbalance (FD-IQI & FI-IQI) are explored in this paper. In order to reduce implementation complexity, we propose sequential compensation rather than...
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