Linear discriminant analysis (LDA) is one of the most popular methods of classification. For high-dimensional microarray data classification, due to the small number of samples and large number of features, classical LDA has sub-optimal performance corresponding to the singularity and instability of the within-group covariance matrix. Two modified LDA approaches (MLDA and NLDA) were applied for...

In this paper, we present a new approach for fingerprint classification based on Discrete Fourier Transform (DFT) and nonlinear discriminant analysis. Utilizing the Discrete Fourier Transform and directional filters, a reliable and efficient directional image is constructed from each fingerprint image, and then nonlinear discriminant analysis is applied to the constructed directional images, re...

Face descriptor is a critical issue for face recognition. Many local face descriptors like Gabor, LBP have exhibited good discriminative ability for face recognition. However, most existing face descriptors are designed in a handcrafted way and the extracted features may not be optimal for face representation and recognition. In this paper, we propose a learning based mechanism to learn the dis...

OBJECTIVE To describe the development of a new clinically applicable method for assessing vestibular function in humans with particular application in Meniere's disease. STUDY DESIGN Sophisticated signal-processing techniques were applied to data from human subject undergoing tilts stimulating the otolith organs and semicircular canals. The most sensitive representatives of vestibular functio...

we present a novel and e±cient scheme that selects a minimal set of effective features and channels for detecting the p300 component of the event-related potential in the brain-computer interface (bci) paradigm. for obtaining a minimal set of effective features, we take the truncated coe±cients of discrete daubechies 4 wavelet, and for selecting the effective eeg channels, we utilize an improve...

This paper proposes a novel face recognition method based on discriminant analysis with Gabor tensor representation. Although the Gabor face representation has achieved great success in face recognition, its huge number of features often brings about the problem of curse of dimensionality. In this paper, we propose a 3rd-order Gabor tensor representation derived from a complete response set of ...

This paper presents a novel texture-based algorithm for detecting certain kinds of meningiomas in images of neurosurgical resections. The algorithm employs Discriminant Wavelet Packet Transform (DWPT) and Learning Vector Quantization (LVQ). The adaptive DWPT of a test image is computed by maximizing the discrimination power of subbands during the basis selection process for the training images....

This study presents an appearance-based face recognition scheme called the nonparametric-weighted Fisherfaces (NW-Fisherfaces). Pixels in a facial image are considered as coordinates in a high-dimensional space and are transformed into a face subspace for analysis by using nonparametric-weighted feature extraction (NWFE). According to previous studies of hyperspectral image classification, NWFE...

In this paper we explore the effect of long-span features, resulting from concatenating multiple speech frames and projecting the resulting vector onto a subspace using Linear Discriminant Analysis (LDA) techniques. We show that LDA is not always effective in selecting the optimal combination of long-span features, and introduce a discriminative feature analysis method that seeks to minimize ph...