Feature selection is very much useful to choose a subset of features from data set containing more than 100 to 1000 attributes by eliminating irrelevant features to improve predictive information. Feature selection is the most promising field of research in data mining in which most impressive achievements have been reported. The feature selection influences the predictive accuracy of any data ...

AbstractAccuracy in identifying the subjects’ intentions for moving their different limbs from EEG signals is regarded as an important factor in the studies related to BCI. In fact, the complexity of motor-imagination and low amount of signal-to-noise ratio for EEG signal makes this identification as a difficult task. In order to overcome these complexities, many techniques such as variou...

Histograms are commonly used in content-based image retrieval systems to represent the distributions of colors in images. It is a common understanding that histograms that adapt to images can represent their color distributions more efficiently than do histograms with fixed binnings. However, existing systems almost exclusively adopt fixed-binning histograms because, among existing well-known d...

Automatic road network extraction based on high resolution satellite image for urban planning holds great potential for significant reduction of database development/updating cost and turnaround time. Satellite remote sensing has been recognized worldwide as an effective technology for the monitoring and mapping the urban development. Two approaches for road network extraction for an urban regi...

Kalman Filter (KF) based algorithms are the most frequently employed attitude estimation algorithms. Typically, a fully observable system necessitates use of two distinct sensor types. Therefore, relying on single sensor, such as magnetometer, for spacecraft is deemed to be challenge. The present investigation centers utilizing magnetometers exclusive sensor. Several KF have been designed and e...

In this paper we present a general formalism for the establishment of the family of selective partial update affine projection algorithms (SPU-APA). The SPU-APA, the SPU regularized APA (SPU-R-APA), the SPU partial rank algorithm (SPU-PRA), the SPU binormalized data reusing least mean squares (SPU-BNDR-LMS), and the SPU normalized LMS with orthogonal correction factors (SPU-NLMS-OCF) algorithms...

Since the introduction of the median filter by John Tukey in 1971, many important classes of order statistic-based nonlinear filters have bccn developed. In this papcr we review some rcccnt results obtained for the two filter classes known as stack filters and weighted median filters. The highlights include new results on optimal filter design and fast training algorithms. .

In this paper Adaptive filter is designed and simulated using different algorithms for noise reduction in different signals. The developed filter has been analyzed using Least Mean Square (LMS), Normalized Least Mean Square (NLMS) and Recursive Least Squares (RLS) algorithms for sinusoidal, chirp and saw-tooth signals. The performance of developed filter has been compared interms of Rate of Con...