Design and implementation of signal processing algorithms and architectures for communication and other applications

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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 is to develop efficient algorithms and architectures and to lay sound mathematical foundations for reliable processing of speech, image/video, image and genomic signals, and for their efficient software and hardware implementations for multimedia communication and other 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. 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 the design and implementation of DSP algorithms that are cost effective and superior in performance. Regulation of gene expressions is a dynamic process. Understanding of the gene interactions that contribute to certain diseases provide valuable information for pharmaceutical and biotechnology industries. Signal processing techniques for the analysis of genomic signals and for modeling of the dynamics of gene regulation will be developed. 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. Fast and efficient techniques for computing these transforms will be undertaken. Research efforts will also be directed towards efficient software and VLSI implementations of the algorithms developed in this proposal.