Digital Signal Processing

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CHAPTER I INTRODUCTION On systems that perform real-time processing of data, performance is often limited by the processing capability of the system [1]. Therefore, in order to judge the efficiency of any system it is very important that we evaluate the performance of the architectures based on which the system is being built. We can also state that we can make a system more efficient and more capable by working upon the algorithm on which the system is being built. The more efficient the algorithm is the more efficient will be our system and vice versa. It is assumed that the way in which this chapter is written will provide the source of motivation for the thesis, it will also give an insight of the work which is done and it is organized in the thesis. 1.1 Motivation Digital signal processing (DSP) has been a major player in the current technical advancements such as noise filtering, system identification, and voice prediction [2]. But, standard DSP techniques, are not equipped enough to solve these problems effectively and obtain almost desirable results. Adaptive filtering is an answer to the problem and is being implemented to promote accurate solutions and a timely convergence to that solution. Therefore, because of the high end capabilities of the adaptive techniques these are being widely implemented in the fields like radar, communications, seismology, mechanical design and biomedical electronic equipments. No matter how sophisticated adaptive
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