Signal processing algorithms for applications in communication systems

数字信号处理（DSP）领域在过去的几十年里经历了爆炸式的增长。DSP技术已经成为我们日常生活中需要或遇到的产品和服务的组成部分。申请人在过去五年中的研究工作取得了一些非常具体的成果，与国际学术界和工业界的科学界分享，并产生了新的想法和方向，需要进一步研究。建议的研究的总体目标是开发高效的算法，并建立可靠的语音，图像和视频信号的处理，并为多媒体通信应用程序的高效的软件和硬件实现的基本数学基础。在图像的采集、压缩、存储、传输和再现过程中，加性或乘性噪声对图像的失真是很常见的。噪声的存在使得图像数据的自动解释非常困难。语音激活检测、噪声污染语音的基音估计以及含噪语音系统的识别和建模对于语音通信系统的可靠设计至关重要。新兴的通信和信息网络处理大量的数字语音、图像和视频信号，并通过过于拥挤的通信渠道进行传输。这些活动的基础是信号压缩，以及这些信号的预处理和后处理。将努力达到解决这些问题，通过设计和实现的DSP算法，是成本效益和性能优越的上级。离散变换对于信号处理任务是必不可少的。为此，将研究更有效地利用信号的内在特性的新变换。将采用快速有效的技术来计算这些和现有的变换。研究工作也将针对有效的软件和VLSI实现本提案中开发的算法。

The field of digital signal processing (DSP) has experienced an 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 during the past five years have led to some very concrete results that have been shared with 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 is to develop efficient algorithms and to establish the underlying mathematical foundations for reliable processing of speech, image and video signals, and for their efficient software and hardware implementation for multimedia communication applications. The distortion of images by additive or multiplicative noise is common during their acquisition, compression, storage, transmission and reproduction. Presence of the noise makes the automatic interpretation of image data very difficult. Voice activity detection, pitch estimation of noise-corrupted speech, and identification and modeling of noisy speech systems are vital for reliable design of speech communication systems. Emerging communication and information networks deal with high volumes of digital speech, image and video signals and with their transmission through over-congested communication channels. Fundamental to these activities are the signal compression, and pre- and post-processing of such signals. Efforts will be put to reach solutions to these problems through design and implementation of DSP algorithms that are cost effective and are superior in performance. Discrete transforms are essential to signal processing tasks. To this end, new transforms exploiting more efficiently the intrinsic properties of signals will be investigated. Fast and efficient techniques for computing these and the existing transforms will be undertaken. Research efforts will also be directed towards efficient software and VLSI implementations of the algorithms developed in this proposal.