Signal Processing Study Guide: Fourier Analysis, Fft Algorithms, Impulse Response, Laplace Transform, Transfer Function, Nyquist Theorem, Z-Transform, Dsp Techniques, Image Proc. & More (Mobi Study Guides)

Boost Your grades with this illustrated Study Guide. You will use it from an undergraduate school all the way to graduate school and beyond. FEATURES:- Clear and concise explanations - Difficult concepts are explained in simple terms - Illustrated with graphs and diagrams - Search for the words or phrases - Access the guide anytime, anywhere - at home, on the train, in the subway. - Use your down time to prepare for an exam. - Always have the guide available for a quick reference. TABLE OF CONTENTS: I. Foreword II Mathematical Analysis III. DSP Theory IV. DSP Sub-fields V. DSP Techniques VI. Sampling VII. Statistical Signal Processing VIII. Image processing IX. Control engineering X. DSP Architecture I. Foreword About Signal Processing About Digital signal processing II. Mathematical Analysis Fourier analysis Fourier series Fourier transform Fast Fourier transform Gibbs phenomenon Impulse response Laplace transform Two-sided Laplace transform Transfer function Dirac comb Dirac delta function Sinc function Goertzel algorithm Abel transform Spline interpolation Stochastic differential equation III. DSP Theory Nyquist-Shannon sampling theorem Whittaker-Shannon interpolation formula Estimation theory Detection theory LTI system theory IV. DSP Sub-fields Audio signal processing Digital image processing Speech processing Statistical signal processing Image processing Control engineering V. DSP Techniques Discrete Fourier transform (DFT) Bilinear transform Z-transform Aadvanced Z-transform Discrete cosine transform Modified discrete cosine transform VI. Sampling Sampling Digital frequency Quantization Companding Signal reconstruction Aliasing Reconstruction filter Negative frequency VII. Statistical Signal Processing Bayes theorem Bayes estimator Recursive Bayesian estimation Wiener filter Kalman filter Fast Kalman filter Adaptive filter Finite impulse response Statistical classification Hidden Markov models VIII. Image processing Principal components analysis Independent component analysis Self-organizing maps Neural networks Computer vision Affine shape adaptation Blob detection Lanczos resampling Tomographic reconstruction IX. Control engineering Adaptive control Building Automation Control reconfiguration Feedback H infinity Intelligent control Laplace transform Model predictive control Non-linear control Optimal control Process control Quantitative feedback theory Robotic unicycle Robust control Servomechanism State space VisSim X. DSP Architecture Digital signal processor von Neumann architectur