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Applied Topological Signal Processing with Python: Persistent Homology and Feature Extraction for Temporal Data - Softcover

Marwood, Helena K.

 
9798176996296: Applied Topological Signal Processing with Python: Persistent Homology and Feature Extraction for Temporal Data
Softcover
ISBN 13: 9798176996296
Verlag: Independently published, 2026

Inhaltsangabe

Reactive Publishing

Traditional signal processing relies heavily on Fourier transforms and time-frequency methods—tools that often fail when dealing with non-stationary, noisy, or high-dimensional real-time data. Applied Topological Signal Processing with Python bridges the gap between abstract mathematical topology and practical engineering, providing a hands-on guide to analyzing complex temporal data streams.

This book delivers a concrete framework for implementing Topological Data Analysis (TDA) directly in real-world signal workflows. Through complete Python examples, you will learn how to transform raw physical measurements and time-series arrays into persistence diagrams, extract robust structural features, and strip out background noise without losing critical phase information.

Inside, you will explore:

  • Fundamentals of Persistent Homology: Construct Vietoris-Rips and filtration complexes from numerical time-series.

  • Noise Reduction & Filtering: Separate true topological signal signatures from random ambient noise.

  • Feature Vectorization: Convert persistence landscapes and diagrams into ML-ready inputs for Scikit-Learn and PyTorch models.

  • Real-Time Signal Workflows: Implement sliding-window algorithms designed for streaming data pipelines.

  • Python Tooling: Practical implementations using Gudhi, Ripser, SciPy, and NumPy.

Whether you are a data scientist working with sensor networks, a biomedical engineer analyzing ECG/EEG signals, or a quantitative developer processing financial ticks, this text provides the exact code patterns and mathematical foundations needed to deploy topological methods into production.

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Verlag
Independently published
Erscheinungsdatum
2026
Sprache
Englisch
ISBN 13 
9798176996296
Einband
Taschenbuch
Anzahl der Seiten
444
Herausgeber
Schwartz Alice
Kontakt zum Hersteller
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