Outline
- Foundations
- Signals Represent Information
- Introduction to Systems
- Discrete-Time Signals and Systems
- Linear Time-Invariant Systems
- Discrete-Time Convolution
- Review of Linear Algebra
- Hilbert Spaces
- Signal Expansions
- Fourier Analysis
- Continuous-Time Fourier Transform (CTFT)
- Discrete-Time Fourier Transform (DTFT)
- DFT as a Matrix Operation
- The FFT Algorithm
- Solutions
- Sampling and Frequency Analysis
- Introduction
- Proof
- Illustrations
- Sampling and Reconstruction with Matlab
- Systems View of Sampling and Reconstruction
- Sampling CT Signals: A Frequency Domain Perspective
- The DFT: Frequency Domain with a Computer Analysis
- Discrete-Time Processing of CT Signals
- Short Time Fourier Transform
- Spectrograms
- Filtering with the DFT
- Image Restoration Basics
- Solutions
- Digital Filtering
- Difference Equation 103
- The Z Transform: Definition
- Table of Common z-Transforms
- Understanding Pole/Zero Plots on the Z-Plane
- Filtering in the Frequency Domain
- Linear-Phase FIR Filters
- Filter Structures
- Overview of Digital Filter Design
- Window Design Method 125
- Frequency Sampling Design Method for FIR Filters
- Parks-McClellan FIR Filter Design
- FIR Filter Design using MATLAB
- MATLAB FIR Filter Design Exercise
- Solutions
- Statistical and Adaptive Signal Processing
- Introduction to Random Signals and Processes
- Stationary and Nonstationary Random Processes
- Random Processes: Mean and Variance
- Correlation and Covariance of a Random Signal
- Autocorrelation of Random Processes
- Crosscorrelation of Random Processes
- Introduction to Adaptive Filters
- Discrete-Time, Causal Wiener Filter
- Practical Issues in Wiener Filter Implementation
- Quadratic Minimization and Gradient Descent
- The LMS Adaptive Filter Algorithm
- First Order Convergence Analysis of the LMS Algorithm
- Adaptive Equalization
Solutions
Glossary
Bibliography
Index
Detail here Fundamentals of Signal Processing
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