Digital Signal Processing Lecture Notes by University of Washington

Digital Signal Processing Lecture Notes by University of Washington

Digital Signal Processing Lecture Notes by University of Washington

This note covers the following topics: LTI systems, Freq.
Response, DTFT, convergence, FT properties, FT pairs, random signals,
z-transform, ROC and properties of z-transform of sequences, z-Transform
properties, sampling and Nyquist sampling theorem, Signal reconstruction, DT vs.
CT processing, Multirate signal processing, Generalized linear phase and FIR
types, Filter design, Minimum phase systems and generalized linear phase, IR
filter design by windowing, Kaiser window and optimal approximation, Optimal
approximations of FIR filters, Discrete Fourier Series.

This note will
introduce the basic concepts and techniques for processing discrete-time signal
on a computer. Topics covered includes: discrete-time signals and systems,
Fourier transforms and frequency response, Z-Transform, Sampling and
reconstruction, Transform analysis of LTI systems, System structures and
implementation, IIR filter design, FIR filter design, The discrete Fourier
transform, The fast Fourier transform and FFT analysis.

This
note covers the following topics: DT Signals and Systems, Z Transform, Using ZT
to Analyze DT LTI Systems , DTFT, Sampling Theory, MATLAB, DFT Processing,
Filter Design.

This note
explains the following topics: DT Fourier Transform, Sampling, CT Signal
Reconstruction, The Discrete Fourier Transform, Applications of the DFT, DT
Systems and the ZT, Analog Filter Design, IIR Filters, FIR Filters.

This note covers the following
topics: Applications of DSP, Power and Energy Signals, Properties Of LTI System,
Discrete Convolution, Properties Of DFS, Fourier Transform Of Discrete Time
Signals, DFT (Frequency Domain Sampling), FFT, Digital Filter Structure,
Butterworth Filter Design, Chebyshev Filter Design, Impulse Invariance Method.

This note teaches the
basic signal-processing principles necessary to understand many modern high-tech
systems, with a particular view on audio-visual data compression techniques.
Topics covered includes: Signals and systems, Phasors, Fourier transform,
Discrete sequences and spectra, Discrete Fourier transform, Spectral estimation,
Finite and infinite impulse-response filters, Random sequences and noise,
Correlation coding, Lossy versus lossless compression, Quantization, image and
audio coding standards.

This note
begins with a discussion of the analysis and representation of discrete-time
signal systems, including discrete-time convolution, difference equations, the
z-transform, and the discrete-time Fourier transform. Emphasis is placed on the
similarities and distinctions between discrete-time. It proceeds to cover
digital network and nonrecursive digital filters.

The focus of this book is on
spectral modeling applied to audio signals. More completely, the principal tasks
are spectral analysis, modeling, and resynthesis (and/or effects). It mainly
covers the following topics: Fourier Transforms and Theorems, Spectrum Analysis
Windows, FIR Digital Filter Design, Spectrum Analysis of Sinusoids, Spectrum
Analysis of Noise, Overlap-Add STFT Processing, Filter Bank View of the STFT,
Applications of the STFT, Multirate Filter Banks and Continuous Fourier
Theorems.

This note covers
the following topics: Signal Types, Signal Characteristics, Signal
Transformations, Special Signals, Frequency analysis, Z-transform, DFT and FFT
and Random sequences.