Biometric systems have the goal of measuring and analyzing the unique physical or
behavioral characteristics of an individual. The main feature of biometric systems is the use …

The aim of this paper is to collect in one place the basic background needed to understand
the discriminant analysis (DA) classifier to make the reader of all levels be able to get a …

Linear Discriminant Analysis (LDA) is a very common technique for dimensionality reduction
problems as a preprocessing step for machine learning and pattern classification …

Statistical pattern recognition is a very active area of study andresearch, which has seen
many advances in recent years. New andemerging applications-such as data mining, web …

Electrocardiogram (ECG) has extremely discriminative characteristics in the biometric field
and has recently received significant interest as a promising biometric trait. However, ECG …

Heterogeneous face recognition (HFR) involves matching two face images from alternate
imaging modalities, such as an infrared image to a photograph or a sketch to a photograph …

The problem of matching a forensic sketch to a gallery of mug shot images is addressed in
this paper. Previous research in sketch matching only offered solutions to matching highly …

Dimensionality reduction is an important aspect in the pattern classification literature, and
linear discriminant analysis (LDA) is one of the most widely studied dimensionality reduction …

Abstract Linear Discriminant Analysis (LDA) is a popular technique for supervised
dimensionality reduction, and its performance is satisfying when dealing with Gaussian …

Common spatial pattern (CSP) is a popular algorithm for classifying electroencephalogram
(EEG) signals in the context of brain-computer interfaces (BCIs). This paper presents a …