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

通信、生物医学等领域数字信号处理算法的设计与实现 数字信号处理(DSP)领域在过去的几十年里经历了爆炸性的增长。数字信号处理技术已经成为我们日常生活中所需要或遇到的产品和服务不可或缺的一部分。申请者在过去五年中在这一领域的研究努力取得了一些非常具体的成果，这些成果已与国际科学界分享，包括学术界和工业界，并产生了需要进一步研究的新想法和新方向。拟议研究计划的总体目标是开发高效的算法和体系结构，并为图像、视频、生物医学和基因组信号的可靠处理以及通信、生物医学和其他应用的成本效益实现奠定坚实的数学基础。离散变换对于信号处理任务是必不可少的。为此，将研究能够优化给定应用程序的性能的新的参数化变换。噪声的存在使得图像数据的自动内插变得非常困难。另一个令人担忧的问题是图像数据的安全性。这项研究将研究各种信号变换和变换后的图像数据的统计模型在寻找有效的去噪和水印问题的解决方案方面的适用性。图像和视频中的目标检测和跟踪在监控、交通管理和细胞生物学中有着重要的应用。将开展一项研究，以开发适用于基于检测的目标跟踪的协作模型。细胞周期自动分析在新药发现和生命科学研究中具有重要意义。这项研究的目的是在信号处理框架内开发对延时显微图像中细胞不同阶段的检测、跟踪和识别，以实现细胞周期分析的自动化，同时应对细胞聚集、变形和不均匀运动的挑战。蛋白质是生物体中最重要的分子，参与细胞的信号传递、代谢调节、分子运输和防御机制等各项功能。氨基酸的插入和缺失是导致蛋白质序列进化和变异的常见事件。这项研究将致力于通过利用蛋白质序列中插入/缺失区域的信息来开发多个蛋白质序列比对的信号处理技术。使用可靠的个人识别码是打击身份欺诈的必要手段。为了提高多通道生物识别系统的识别率，本研究将研究多个生物特征在分数级和特征级的融合。

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.