Digital Signal Processing Theory and Applications

Digital signal processing (DSP) is the mathematical manipulation of an information signal to modify or improve it in some way. It is characterized by the representation of discrete time, discrete frequency, or other discrete domain signals by a sequence of numbers or symbols and the processing of these signals. The goal of DSP is usually to measure, filter and/or compress continuous real-world analog signals. The DSP applications include audio and speech signal processing, sonar and radar signal processing, sensor array processing, spectral estimation, statistical signal processing, digital image processing, signal processing for communications, control of systems, biomedical signal processing, siesmic data processing, etc. This book contains nine chapters. First chapter deals with theory and application of homomorhpic encryption. The overall process to code a digital hologram video and the whole architecture of the service system for digital holograms are explained in second chapter. Chapter third provides a profound discussion on a filter bank structure to yield an effective scheme in computation in such complex processing. Fourth chapter describes the optimized signal processing for 3d-polarized light imaging. Chapter fifth focuses on the evaluation of the performances of different antenna sensors suitable for partial discharge digital signal processing probes. In sixth chapter, the SAR and optical techniques applied to produce DEMs were introduced, leading to the topic of elevation data fusion. We address the problem of finding the optimal-minimum cost-configuration of a logical topology over a fixed physical layer in seventh chapter. Eight chapter gives the details of real-time video encoding scheme based on the contourlet transform. Last chapter proposes a new method to overcome these limitations by using ID signal analysis methods.