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C. Sidney Burrus

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Type Title
Higher Order Model
Horner's Method for Evaluating and Deflating Polynomials
Implementing Kronecker Products Efficiently
Introduction
Introduction: Fast Fourier Transforms
Large DFT Modules: 11, 13, 16, 17, 19, and 25
Least Squared Error Design of FIR Filters
Limits to Growth
Linear Algrebra for Signals and Systems: A Matrix times a Vector
m01 - An Overview of Continuous-Time Signals
m01 - FIR Digital Filters Overview
m02 - The Fourier Series
m03 - Properties of the Fourier Series
m04 - Theorems on the Fourier Series
m05 - The Fourier Transform
m06 - Properties of the Fourier Transform
m07 - The Laplace Transform
m08 - Properties of the Laplace Transform
m09 - An Overview of Discrete-Time Signals
m10 - The Discrete Fourier Transform
m11 - Properties of the DFT
m12 - The Discrete-Time Fourier Transform
m13 - Properties of the DTFT
m14 - Evaluation of the DTFT by the DFT
m15 - The Z-Transform
m16 - Properties of the Z-Transform
m17 - Solution of Difference Equations using the Z-Transform
m18 - Region of Convergence for the Z-Transform
m19 - Wavlet-Based Signal Analysis
m20 - An Overview of Discrete-Time Systems
m20.5 - Classifications of Signal Processing Systems
m21 - Convolution of Discrete-Time Signals
m22 - The Z-Transform Transfer Function
m23 - Frequency Response of Discrete-Time Systems
m24 - Sampling
m25 - Fourier Techniques for Sampling
m26 - Calculation of the Fourier Transform and Fourier Series using the FFT
m27 - The Shah Function
m28 - Upsampling, Signal Stretching and Interpolation
m29 - Downsampling, Subsampling and Decimation
Mathematical Principles for the LF Algorithm
Models
More Details on the Third Stage of the LF Algorithm
Multidimensional Index Mapping
N = 11 Winograd FFT module
N = 13 Winograd FFT module
N = 16 FFT module
N = 17 Winograd FFT module
N = 17 Winograd FFT module in C
N = 19 Winograd FFT module
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