Studies in signal processing with applications

在过去的25年里，数字信号处理(DSP)技术在生物医学信号处理、声学、电信、图像和视频信号处理以及地震学等不同领域中得到了广泛的应用。高精度、低成本、高速A/D转换器和功能强大的VLSI数字信号处理器的出现，为DSP在这些领域不断扩大的应用提供了必要的动力。多维(m-D)DSP技术正越来越多地被用于处理m-D信号，例如从卫星、X射线和其他来源获得的图像和运动图像。视频电话和高清晰度电视是从2-D和3-D数字信号处理器领域的研究和开发进展中获得的一些产品。拟议研究的总体目标是开发各种高效和可靠的算法来过滤和处理信号(如图像、视频、语音和生物医学信号)。特别是，我们将在未来5年集中开展以下项目。(A)我们建议发展一套智能监察系统，以侦测、分类和识别人类的行动，并只在有需要时才要求人类注意。这种系统可用于家庭和建筑物监控、停车场监控等。它可以通过确定偏远地区患者或老年人的病情来增强卫生服务。(B)开发用于图像处理的二维近正交对称小波滤波器组。(C)将压缩感知应用于半盲或盲信道估计，这在基于MIMO-OFDM技术的未来4G系统中以及在接收器数量少于传感器数量时的到达方向估计中起着关键作用。(D)在余数系统的帮助下，为密码功能设计低功耗和容错的嵌入式数字系统。(E)开发用于生物医学应用的算法。这些项目的成果将有利于电信、医疗信号处理、VLSI、图像和视频信号处理以及该行业的无线部门。

Digital signal processing (DSP) techniques have found a variety of applications over the last 25 years in processing of signals in such diverse areas as biomedical signal processing, acoustics, telecommunications, image and video signal processing, and seismology. The availability of high-resolution, inexpensive, high-speed A/D converters and powerful digital signal processors in VLSI form has provided the necessary impetus for the ever-expanding applications of DSP in these areas. Multidimensional (m-D) DSP techniques are being increasingly used in the processing of m-D signals such as pictures and moving pictures obtained from satellites, x-rays, and other sources. Videophone and HDTV are some examples of products that have gained from the research and development advances in the 2-D and 3-D DSP area. The overall objectives of the proposed research are to develop a variety of efficient and reliable algorithms for filtering and processing of signals (such as image, video, speech, and biomedical signals). In particular, we will concentrate over the next 5 years on the following projects. (a) We propose to develop an intelligent surveillance system with the ability to detect, categorize and recognize human action, and ask for human attention only when necessary. Such a system could be used for home and building surveillance, parking lot monitoring, etc. It can enhance the health services by determining the condition of a patient or elderly people in a remote area. (b) Development of 2-D nearly orthogonal symmetric wavelet filter banks for use in image processing. (c) Application of compressed sensing for semi-blind or blind channel estimation, which plays a key role in the future 4G systems that are based on MIMO-OFDM technology, as well as in the direction of arrival estimation when the number of receivers is less than the number of sensors. (d) To devise low-power and fault tolerant embedded digital systems for cryptographic functions with the help of the residue number system. (e) Development of algorithms for biomedical applications. The results from these projects should be beneficial to the telecommunication, medical signal processing, VLSI, image and video signal processing, and wireless sectors of the industry.