HarmoniX reveals the stable heartbeat of your data
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| Format: | Recurso digital |
| Sprache: | Englisch |
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Zenodo
2025
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| _version_ | 1866902304857260032 |
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| author | Blankert, Jean Philippe |
| author_facet | Blankert, Jean Philippe |
| contents | <h3>Discover Hidden Harmonics in Your Data with <strong>HarmoniX</strong></h3> <p><strong>HarmoniX</strong> is a next-generation signal analysis operator designed to uncover <strong>subtle, stable periodic patterns</strong> where traditional methods like Fourier fall short. Whether you're analyzing <strong>financial time-series</strong>, <strong>biomedical signals</strong>, or <strong>acoustic data</strong>, HarmoniX excels in separating meaningful structure from volatile noise.</p> <h4>✅ Why Choose HarmoniX?</h4> <ul> <li> <p><strong>Detects rhythmic structure</strong> even in noisy, non-stationary signals</p> </li> <li> <p><strong>Suppresses spikes and transients</strong> that distort classical frequency analysis</p> </li> <li> <p><strong>Ideal for irregular data</strong> — from heartbeats to high-frequency trading signals</p> </li> <li> <p><strong>Mathematically elegant</strong> and easy to implement in Python or embedded systems</p> </li> </ul> <h4> Use Cases</h4> <ul> <li> <p><strong>Finance:</strong> Spot recurring market patterns masked by volatility</p> </li> <li> <p><strong>Healthcare:</strong> Detect arrhythmias or periodic neural signals with precision</p> </li> <li> <p><strong>Audio Processing:</strong> Isolate consistent harmonic content in speech or music</p> </li> <li> <p><strong>Engineering:</strong> Monitor stable oscillatory behaviors in complex machinery</p> </li> </ul> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15555435 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | HarmoniX reveals the stable heartbeat of your data Blankert, Jean Philippe <h3>Discover Hidden Harmonics in Your Data with <strong>HarmoniX</strong></h3> <p><strong>HarmoniX</strong> is a next-generation signal analysis operator designed to uncover <strong>subtle, stable periodic patterns</strong> where traditional methods like Fourier fall short. Whether you're analyzing <strong>financial time-series</strong>, <strong>biomedical signals</strong>, or <strong>acoustic data</strong>, HarmoniX excels in separating meaningful structure from volatile noise.</p> <h4>✅ Why Choose HarmoniX?</h4> <ul> <li> <p><strong>Detects rhythmic structure</strong> even in noisy, non-stationary signals</p> </li> <li> <p><strong>Suppresses spikes and transients</strong> that distort classical frequency analysis</p> </li> <li> <p><strong>Ideal for irregular data</strong> — from heartbeats to high-frequency trading signals</p> </li> <li> <p><strong>Mathematically elegant</strong> and easy to implement in Python or embedded systems</p> </li> </ul> <h4> Use Cases</h4> <ul> <li> <p><strong>Finance:</strong> Spot recurring market patterns masked by volatility</p> </li> <li> <p><strong>Healthcare:</strong> Detect arrhythmias or periodic neural signals with precision</p> </li> <li> <p><strong>Audio Processing:</strong> Isolate consistent harmonic content in speech or music</p> </li> <li> <p><strong>Engineering:</strong> Monitor stable oscillatory behaviors in complex machinery</p> </li> </ul> |
| title | HarmoniX reveals the stable heartbeat of your data |
| url | https://doi.org/10.5281/zenodo.15555435 |