Design and Implementation of Digital Signal Processing Algorithms for Communication, Biomedical and other Applications

点击翻译按钮获取中文摘要

Design and Implementation of Digital Signal Processing Algorithms for Communication, Biomedical and other Applications The field of digital signal processing (DSP) has experienced explosive growth during the past couple of decades. The DSP techniques have become integral parts of the products and services that we need or encounter in our daily lives. The research efforts of the applicant in this area during the past five years have led to some very concrete results that have been shared with the international scientific community, both from academia and industry, and have given rise to new ideas and directions that need to be further investigated. The overall objective of the proposed research program is to develop efficient algorithms and architectures and to lay sound mathematical foundations for reliable processing of image, video, biomedical and genomic signals, and cost-effective implementations for communication, biomedical and other applications. Discrete transforms are essential to signal processing tasks. To this end, new parameterized transforms capable of optimizing the performance of given applications will be investigated. Presence of noise makes the automatic interpolation of image data very difficult. Another concern is the security of the image data. This research will investigate the suitability of the various signal transforms and the statistical models of the transformed image data in finding effective solutions to the problems of denoising and watermarking. Object detection and tracking in images and videos have important applications in surveillance, traffic management and in cell biology. A study to develop a suitable collaborative model for detection based object tracking will be undertaken. Automatic cell cycle analysis is important for discovery of new drugs and in life science research. This research will aim at developing in a signal-processing framework the detection, tracking and identification of the different phases of cells in time-lapse microscopic images to automate cell cycle analysis while meeting challenges of clustering, deformation and uneven motion of cells. Proteins are the most important molecules in living organisms as they are involved in every function of the cells such as signal transmission, metabolic regulation, transportation of molecules and defense mechanism. Insertion and deletion of amino acids are common events that lead to the evolution and variations in protein sequences. This research will focus on developing signal processing techniques for alignment of multiple protein sequences by employing the information on insertion/deletion regions in the protein sequences. Use of a reliable personal identifier is a necessary to fight identity fraud. This research will investigate the score-level and feature-level fusions of multiple biometric traits in order to improve the recognition rate of multimodal biometric systems.