Entropy functions for real valued signal, such as EEG, ECG, Speech.
Applications:Signal Complexity Analysis, Noise-level detection
Methods:
Sample & Aproximate Entropy,
Dispersion Entropy,
Mutual Information, Cross-entropy,
Differential Entropy,
and more...
Time-Frequency Analysis usign Continues and Discrete Wavelet transforms
Applications: Arfticat Removal Algorithms, De-noising Signals.
Methods/Algorithms:
Wavelet Filtering,
CWT,
Decomposed Signals,
ATAR- Artifact Removal for EEG,
and more...
Signal Processing techniques specifically for biomedical signals such as EEG, GSR, ECG, EGM, MEA.
Applications: Artifact removal techniques, Microelectrode Array
Methods:
EEG Signal Processing,
MEA: Microelectrode-Array Processing,
ATAR-Algorithm,
Biomedical Samples,
and more...
Analysis and Sythesis Models: Transforming signals to different space: Sinusoidal Model, DCT, PCA, ICA, Signal decomposition models
Applications: Simplifying signals, Complexity analysis, Feature extractions
Methods/Algorithms:
Sinusoidal Model,
Fractional Fourier Transform,
DFT/STFT,
and more...
More Signal Analysis Methods: Feature extraction, Non-linear mapping, normalisation.
Applications: Transforming and analysing signals for Statistics and machine learning.
Algorithms:
Period Estimation with Ramanujan Methods,
Quantize Signal,
Phase Mapping,
Dominent Frequency Analysis,
and more...
Machine Learing models with detailed visualisations
Applications: Visualization, Increased insight
Methods:
Logistic Regression,
Naive Bayes,
Shrinking Capability of Decision Trees,
Toy Data Simulation,
and more...
