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, Multi-Electrode Array Methods: EEG Signal Processing, MEA: Multielectrode-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...
