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This paper presents a memetic algorithm based new approach to feature selection in face recognition. In this work, principal component analysis (PCA) has been used for dimensionality reduction/feature extraction and memetic algorithms have been applied for selection of features in face recognition application. ORL face database has been used for performing(More)
In this paper, we propose a new detection scheme, which can be used to remove the inherent permutation and scaling ambiguities of the ICA algorithms used for blind source separation. This has the advantage of enhancing the performance of the ICA algorithms when applied for detection of DS-CDMA signals. ICA based techniques are based on independence of(More)
Unsupervised or Self-Organized learning algorithms have become very popular for discovery of significant patterns or features in the input data. The three prominent algorithms namely Principal Component Analysis (PCA), Self Organizing Maps (SOM), and Independent Component Analysis (ICA) have widely and successfully been used for face recognition. In this(More)
The performance of a conventional single user DS-CDMA receiver is severely limited by multiple access interference (MAI) and near–far effects. This severity has motivated research into adaptive filtering, near–far resistant detectors and power control strategies for DS-CDMA systems. In this paper, we propose a near–far resistant detector based on(More)
Independent Component Analysis (ICA) is one of the fastest growing fields in the area of neural networks and signal processing. Blind Source Separation (BSS) is one of the applications of ICA. In this paper, ICA has been used for separating unknown source signals. BSS is used to extract independent signal components from their observed linear mixtures at an(More)
There has been huge interest in evaluation of 802.11 networks particularly DCF in recent past among research community. Various analytical models had been proposed for evaluating the performance analysis of 802.11 DCF. These models are based on traffic conditions i.e. either network operates in saturated conditions or non-saturated conditions. In this paper(More)
Data mining is an automated process of discovering knowledge from databases. There are various kinds of data mining methods aiming to search for different kinds of knowledge. Data mining systems induce knowledge from data sets, which are huge, noisy (incorrect), incomplete, inconsistent, imprecise (fuzzy), and uncertain. The problem is that existing systems(More)