2. Modules: Table of Contents

Fig. 2.1 Teaspoon is divided into five modules, roughly corresponding to the steps in a standard topological signal processing pipeline. Details for each module can be found below.

• 2.1. Make Data (MakeData) Module
  • 2.1.1. Point Cloud Data Generation (PointCloud) Module
  • 2.1.2. Dynamical Systems Library (DynSysLib) Module
• 2.2. Parameter Selection Module
  • 2.2.1. Mutual Information (MI) for time delay (tau).
  • MI_DV()
  • MI_basic()
  • MI_for_delay()
  • MI_kraskov()
  • 2.2.2. Auto-correlation for time delay (tau).
  • autoCorrelation_tau()
  • 2.2.3. Statistical analysis of the Fourier spectrum for time delay (tau).
  • AbsFFT()
  • LMSforDelay()
  • MaximumFrequency()
  • 2.2.4. Permutation Auto Mutual Information (PAMI) for time delay (tau).
  • PAMI_for_delay()
  • mutualPerm()
  • 2.2.5. MsPE for time delay (tau) and dimension (n).
  • MsPE_n()
  • MsPE_tau()
  • 2.2.6. False Nearest Neighbors (FNN) for dimension (n).
  • FNN_n()
• 2.3. Signal Processing (SP) Module
  • 2.3.1. Time Series Analysis (TSA) Tools
  • 2.3.2. Network Representation of Time Series
  • 2.3.3. Information Module
  • 2.3.4. Miscellaneous
  • 2.3.5. Texture Analysis
  • 2.3.6. Stochastic P-Bifurcation Detection
• 2.4. Topological Data Analaysis (TDA) Module
  • 2.4.1. Persistent Homology of Networks (PHN) Module
  • 2.4.2. Distances
  • 2.4.3. Drawing
  • 2.4.4. Persistence
  • 2.4.5. Zero Dimensional Sublevel Set Persistence (SLSP) Module
  • 2.4.6. Magnitude
  • 2.4.7. Fast Zigzag
• 2.5. Machine Learning (ML) Module
  • 2.5.1. Datasets
  • 2.5.2. Featurization
  • 2.5.3. Classification
  • 2.5.4. References