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<!DOCTYPE html>
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<h2>Signal Processing Toolkit</h2>
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<li>• EEG Artifact removal algorithms: ATAR and ICA</li>
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<h4><a href="modules/information_theory.html">Information Theory</a></h4>
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<div class="card-body">
<p class="card-text">Entropy functions for real valued signal, such as EEG, ECG, Speech.</p>
<p class="card-text"><strong>Applications:</strong>Signal Complexity Analysis, Noise-level detection</br>
<strong>Methods:</strong>
<a href="modules/it_entropy.html#sample-entropy-approximate-entropy">Sample & Aproximate Entropy</a>,
<a href="modules/it_disperssion_differential.html#dispersion-entropy-h-de-x">Dispersion Entropy</a>,
<a href="auto_examples/information_theory/plot_it_entropy_eeg_multi_channel.html">Mutual Information, Cross-entropy</a>,
<a href="modules/generated/spkit.entropy_differential.html">Differential Entropy</a>,
and <a href="modules/information_theory.html">more...</a></p>
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<h4><a href="modules/spwavelet_analysis.html#wavelet-analysis">Wavelet Analysis</a></h4>
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<p class="card-text">Time-Frequency Analysis usign Continues and Discrete Wavelet transforms</p>
<p class="card-text"><strong>Applications:</strong> Arfticat Removal Algorithms, De-noising Signals.</br>
<strong>Methods/Algorithms:</strong>
<a href="modules/sp_dwt.html#wavelet-filtering-shrinkage">Wavelet Filtering</a>,
<a href="modules/sp_cwt.html#continues-wavelet-transform">CWT</a>,
<a href="modules/generated/spkit.wavelet_decomposed_signals.html">Decomposed Signals</a>,
<a href="auto_examples/electroencephalogram/plot_sp_ATAR_algorithm_tuning.html">ATAR- Artifact Removal for EEG</a>,
and <a href="modules/spwavelet_analysis.html#wavelet-analysis">more...</a></p>
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<h4><a href="modules/biomedical_signals.html">Biomedical Signals</a></h4>
</center>
</div>
<div class="card-body">
<p class="card-text">Signal Processing techniques specifically for biomedical signals such as EEG, GSR, ECG, EGM, MEA.</p>
<p class="card-text"><strong>Applications:</strong> Artifact removal techniques, Microelectrode Array</br>
<strong>Methods:</strong>
<a href="auto_examples/index.html#electroencephalography-eeg">EEG Signal Processing</a>,
<a href="modules/bsp_mea.html">MEA: Microelectrode-Array Processing</a>,
<a href="auto_examples/electroencephalogram/plot_sp_ATAR_algorithm_tuning.html">ATAR-Algorithm</a>,
<a href="modules/data_samples.html#real-world-samples">Biomedical Samples</a>,
and <a href="modules/biomedical_signals.html">more...</a></p>
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<a href="modules/spsignal_analysis.html#signal-analysis" onclick="trackOutboundLink(this);"><span class="link-spanner-header"></span></a>
<div class="card-header">
<center>
<h4><a href="modules/spsignal_analysis.html#signal-analysis">Transform Techniques</a></h4>
</center>
</div>
<div class="card-body">
<p class="card-text">Analysis and Sythesis Models: Transforming signals to different space: Sinusoidal Model, DCT, PCA, ICA, Signal decomposition models</p>
<!-- Techniques not widely available such as Fractional Fourier Transform, Sinusoidal Model, DCT, PCA, ICA, Signal decomposition models.</p> -->
<p class="card-text"><strong>Applications:</strong> Simplifying signals, Complexity analysis, Feature extractions</br>
<strong>Methods/Algorithms:</strong>
<a href="auto_examples/signal_processing/plot_sp_sinusodal_model_example_sound.html#sinusodal-model-synthesis-audio">Sinusoidal Model</a>,
<a href="auto_examples/signal_processing/plot_sp_fractional_fourier_transform.html">Fractional Fourier Transform</a>,
<a href="auto_examples/signal_processing/plot_sp_analysis_sythesis_models.html#analysis-and-synthesis-models">DFT/STFT</a>,
and <a href="modules/spsignal_analysis.html#signal-analysis">more...</a></p>
<center>
<a href="auto_examples/index.html#signal-processing" target="_blank"><img src="_static/cover_transform.jpg" alt="Analysis and Sythesis Models" style="width:90%" /></a>
</center>
</div>
</div>
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<center>
<h4><a href="modules/spsignal_filtering.html">Signal Analysis</a></h4>
</center>
</div>
<div class="card-body">
<p class="card-text">More Signal Analysis Methods: Feature extraction, Non-linear mapping, normalisation.</p>
<p class="card-text"><strong>Applications:</strong> Transforming and analysing signals for Statistics and machine learning.</br>
<strong>Algorithms:</strong>
<a href="auto_examples/signal_processing/plot_sp_RFB_for_period_estimation_with_sparse_penalty.html">Period Estimation with Ramanujan Methods</a>,
<a href="modules/generated/spkit.quantize_signal.html">Quantize Signal</a>,
<a href="modules/generated/spkit.phase_map.html">Phase Mapping</a>,
<a href="modules/generated/spkit.dominent_freq.html">Dominent Frequency Analysis</a>,
and <a href="modules/classes.html#new-methods">more...</a></p>
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