Khaled T. Assaleh

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An evaluation of various classifiers for textindependent speaker recognition is presented. In addition, a new classifier is examined for this application. The new classifier is called the modified neural tree network (MNTN). The MNTN is a hierarchical classifier that combines the properties of decision trees and feedforward neural networks. The MNTN differs(More)
Modern speaker verification applications require high accuracy at low complexity. We propose the use of a polynomialbased classifier to achieve this objective. We demonstrate a new combination of techniques which makes polynomial classification accurate and powerful for speaker verification. We show that discriminative training of polynomial classifiers can(More)
We propose a novel noniterative technique for fetal electrocardiogram extraction. The polynomial networks technique is used to nonlinearly map the MECG signal recorded at the thorax area to the ECG signals recorded at the abdomen. The FECG component is then extracted by subtracting the nonlinearly mapped MECG component from the abdominal ECG signal. Visual(More)
A new set of techniques for using polynomial-based classifiers for speaker identification is examined. This set of techniques makes application of polynomial classifiers practical for speaker identification by enabling discriminative training for large data sets. The training technique is shown to be invariant to fixed liftering and affine transforms of the(More)
The ability to decipher the genetic code of different species would lead to significant future scientific achievements in important areas, including medicine and agriculture. The importance of DNA sequencing necessitated a need for efficient automation of identification of base sequences from traces generated by existing sequencing machines, a process(More)
Base-calling is one of many problems that can be solved using pattern recognition, the act of classifying raw data based on prior or statistical information extracted from the data into various classes. In this paper, we propose a new framework using polynomial classifiers to model electropherogram traces obtained from ABI sequencing machines to perform(More)