Blackledge Digital Signal Processing

Mathematical and Computational Methods, Software Development and Applications
2. Auflage 2006
ISBN: 978-0-85709-945-7
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 840 Seiten

Reihe: Woodhead Publishing Series in Electronic and Optical Materials

This book forms the first part of a complete MSc course in an area that is fundamental to the continuing revolution in information technology and communication systems. Massively exhaustive, authoritative, comprehensive and reinforced with software, this is an introduction to modern methods in the developing field of Digital Signal Processing (DSP). The focus is on the design of algorithms and the processing of digital signals in areas of communications and control, providing the reader with a comprehensive introduction to the underlying principles and mathematical models. - Provides an introduction to modern methods in the developing field of Digital Signal Processing (DSP) - Focuses on the design of algorithms and the processing of digital signals in areas of communications and control - Provides a comprehensive introduction to the underlying principles and mathematical models of Digital Signal Processing

Autoren/Hrsg.

Blackledge, Jonathan M

Leseproben

Notation
Alphabetic an Real coefficients of a Fourier cosine series adjA Adjoint of matrix A A = (aij) Matrix with element at ith row and jth column AT Transpose of A A-1 Inverse of A [A|B] Augmented matrix formed from matrices A and B |A| Determinant of A A(t) Amplitude modulation (amplitude envelope) A(?) Amplitude spectrum bn Real coefficients of a Fourier sine series b Data vector of linear system Ax = b chirp (t) Unit chirp function [with complex form exp(–iat2)] comb(t) Comb function =?ndt-nT] cond(A) Condition number of matrix A (=||A|| × ||A-1||) cn Complex coefficients of a complex Fourier series for example C Capacitance or the contour followed by a path of integration in the z-plane c Data vector associated with linear system x = Mx + c D Fractal dimension or diagonal matrix detA Determinant of A (also denoted by | A |) e Error vector f(t) Arbitrary real function - typically object function or system input f(z) Function of a complex variable | f | modulus of complex variable or function f ||f(t)|| Norm (e.g. a Euclidean norm) of a function f(t) ||fi|| Norm of an array or vector fi ||fi||2 Euclidean norm of array or vector fi ||x||p p-norm of vector x ||x||8 ‘Infinity’ or uniform norm of a vector x ||A|| Norm of matrix A F(?) Complex spectrum of function f(t) Fr(?) Real component of spectrum Fi(?) Imaginary component of spectrum Fi Discrete complex spectrum of discrete function fi g(t) Arbitrary function g(t|t0,?) Green’s function H(t) Tophat function I Unit or identity matrix Im[f] Imaginary part of complex variable or function f k Wavenumber (= 2p/?) L Lower triangular matrix L1 Lower triangular matrix with l’s along the leading diagonal M Iteration matrix associated with linear system x = Mx + c n(t) Noise function ni Discrete noise function Ni Noise spectrum p(t) Instrument function or Impulse Response Function pi Discrete Impulse Response Function P(?) Transfer Function (Fourier transform of pi) Pi Discrete Transfer Function (DFT of pi P(x) Probability density function also denoted by Pr[x(t)] P(a|b) Conditional probability of obtaining a given b P(?) Power spectrum (=| F(?) |2) where F(?) is the Fourier transform of f(t) Pi Discrete power spectrum Pr(x) Probability occurrence of x q Fourier dimension q(t) Quadrature signal R Resistance Ri Denotes the ith row of a matrix Re[f] Real part of complex variable or function f s(t) Real or complex (analytic) signal si Discrete real or complex signal sgn(t) Sign function sinc(t) Sinc function (= sin(t) / t) t Time U Upper triangular matrix U1 Upper triangular matrix with l’s along the leading diagonal U(t) Unit step function u(x,t) Solution to a partial differential equation (e.g. wavefield) vi Eigenvectors of linear system Avi = ?ivi WAL(n, t) Walsh function x Solution vector of linear system Ax = b xi Eigenvectors of linear system Axi = ?ixi xT Transpose of vector x xi ith element of vector x x0 Initial value z Complex number of the form a + ib z* Complex conjugate a – ib of a complex number a + ib ? In (e.g. x ? [a, b) is equivalent to a = x < b) ? Forall (e.g. f (t)= 0, ?t ? (a,b]) Greek a Chirping parameter G(q) Gamma function d(t) Dirac delta function dij Kronecker delta dt Small increment (denoted also by ?t) ?(t) Instantaneous phase ? Wavelength ?i Eigenvalues of linear system Axi = ?ixi ?(t) Instantaneous frequency ?n Delta sequence function ?(M) Spectral radius of (iteration) matrix...