[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8},"actionData","errors","root",{"_29":-5,"_44":-5,"_45":46,"_47":48,"_49":50,"_51":52,"_53":54,"_55":56,"_57":58,"_59":60,"_61":62,"_63":64},"routes/_store+/_readers+/email_author.$slug/route",{"_9":10,"_11":-5},"book",{"_12":13,"_14":15,"_16":17,"_18":19,"_20":21,"_22":23},"currentUser","id","Z2lkOi8vbGVhbnB1Yi9TdG9yZTo6Qm9va1Byb2R1Y3QvNzk4MjU","title","An Introduction to the Discrete Fourier Transform and Its Applications in Signal Processing","state","published","contactAuthorMethod","email","aboutText","

This course monograph provides a progressive introduction to the Discrete Fourier Transform (DFT) and its applications in signal processing. It combines theoretical explanations, numerical examples, and practical implementations in MATLAB and Python/NumPy.

Topics include:

sampling and aliasing;
spectral leakage and windowing;
frequency resolution;
one-sided and two-sided spectra;
phase spectra and fftshift;
FFT implementation and normalization;
practical signal-processing applications.

The material is intended for undergraduate and graduate students, instructors, and engineers who need a clear and operational understanding of spectral analysis and numerical signal processing.

Included with the book:

Complete PDF course monograph;
Executable Jupyter notebook (.ipynb);
HTML version of the course;
High-resolution figures.

The notebook contains all Python/NumPy examples presented throughout the text and allows readers to reproduce, modify, and extend the computations discussed in the monograph.

Companion materials available upon request at (please attach your Leanpub purchase receipt):

signal.processing.course@gmail.com

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Kick off your book project, get started with GhostAI, get better at marketing, or spend the day doing all three! Free live workshops on Zoom. Saturday, June 27, 2026.

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