Digital signal processing : mathematical and computational methods, software development and applications
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Bibliographic Information
Digital signal processing : mathematical and computational methods, software development and applications
Horwood, 2003
- : pbk
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Includes index
Description and Table of Contents
Description
Exhaustive, definitive and comprehensive, this under-graduate introduction to modern methods of Digital Signal Processing (DSP) encapsulates curricula for degree courses in electrical & control engineering, communication systems engineering, applied mathematics and computer science. It emphasises current programming practices and applications of DSP, with focus on designing algorithms and DSP in communications and control. It introduces underlying principles and mathematical models for analysing and processing different types of digital signals. Readers will also gain an understanding of software engineering methodologies used in designing and constructing DSP packages. Case studies in the book are on modelling theory, propagation and scattering of waves, novel cryptography methods, and digital watermarking for IT security.
Table of Contents
- Part I Mathematical Methods for Signal Analysis Introduction to complex analysis
- the delta function and the Green's function
- Fourmet series
- the Fourier transform, convolution and correlation, the sampling theorem, the Laplace transform
- the Hilbert transform and quadrature detection, modulation and demodulation, the wavelet transform, the z-transform, the Wigner transform. Part II Computational Techniques in Linear Algebra Basic linear algebra, types of linear systems, formal methods of solution
- direct methods of solution
- iterative improvement
- vector and matrix norms, conditioning and the condition number, the least squares method
- iterative methods of solution
- the conjugate gradient method
- the computation of eigen values and eigen vectors. Part III Programming and Software Engineering Number systems and numerical error, programming languages, software design methods, structured and modular programming
- software engineering for DSP in C. Part IV Digital Signal Processing
- Methods Algorithms and Building a Library Digital frequency filtering, the DFT and FFT, computing with the FFT, spectral leakage and windowing
- inverse filters, the Wiener filter, the matched filter, constrained deconvolution, homomorphic filtering
- noise and chaos
- Bayesian estimation methods, the maximum entropy method, spectral extrapolation
- FIR and IIR filters, non-stationary signal processing
- random fractal and multi-random-fractal signals.
by "Nielsen BookData"