thinkdsp
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Description
Contents
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Language
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ISBN
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Preface
Who is this book for?
Using the code
Sounds and signals
Periodic signals
Spectral decomposition
Signals
Reading and writing Waves
Spectrums
Wave objects
Signal objects
Exercises
Harmonics
Triangle waves
Square waves
Aliasing
Computing the spectrum
Exercises
Non-periodic signals
Linear chirp
Exponential chirp
Spectrum of a chirp
Spectrogram
The Gabor limit
Leakage
Windowing
Implementing spectrograms
Exercises
Noise
Uncorrelated noise
Integrated spectrum
Brownian noise
Pink Noise
Gaussian noise
Exercises
Autocorrelation
Correlation
Serial correlation
Autocorrelation
Autocorrelation of periodic signals
Correlation as dot product
Using NumPy
Exercises
Discrete Cosine Transform
Synthesis
Synthesis with arrays
Analysis
Orthogonal matrices
DCT-IV
Inverse DCT
The Dct class
Exercises
Discrete Fourier Transform
Complex exponentials
Complex signals
The synthesis problem
Synthesis with matrices
The analysis problem
Efficient analysis
DFT
The DFT is periodic
DFT of real signals
Exercises
Filtering and Convolution
Smoothing
Convolution
The frequency domain
The Convolution Theorem
Gaussian filter
Efficient convolution
Efficient autocorrelation
Exercises
Differentiation and Integration
Finite differences
The frequency domain
Differentiation
Integration
Cumulative sum
Integrating noise
Exercises
LTI systems
Signals and systems
Windows and filters
Acoustic response
Systems and convolution
Proof of the Convolution Theorem
Exercises
Modulation and sampling
Convolution with impulses
Amplitude modulation
Sampling
Aliasing
Interpolation
Summary
Exercises
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