Every part of our live is surrounded by signals hidden behind waves, sounds, images, videos, sensor measurements or simply data series which may be
- the acceleration response of an earthquake
- the dynamics of the ocean tide
- the ecg measurement of a human heart activity
- the magneto-inductive signals analyzed to assess the condition of a rope
- analyze
- code
- transmit
- synthetize
Explore time-frequency information
The analysis consists in dissecting a signal to extract the essential information, the elementary bricks such as notes in a music score, which will inform about the content of the signal. A modern signal analysis tool is to use the wavelet transform or its cousin, the decomposition in a super-resolution wavelet frame to explore the instantaneous frequencies of the signal as a mathematical microscope. Advanced signal exploration — litterally enabling to dive into signals and sometimes to reveal their hidden secrets — makes it possible to analyze
- the instantaneous frequencies associated with anomalies or characteristic features of information
- the shape of the patterns associated with a particular event
- the detection of peaks or singularities of the signal
- the occurrence of complex transients, noise.
The above illustrations make it possible to follow the distribution of the energy of some signals in a scalogram representation with horizontally the time and vertically the frequency
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a purely artificial signal with a complex frequency content
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an ECG electrocardiogram of a patient with an arrhythmia pathology
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a succession of vocalises of a bat (slow x 100)
Transient waves in a clarinet sound
An acoustic researcher asks to analyze with wavelet tools a sound recorded during an experiment with a clarinet. The Fourier spectrum indicates the presence of a note played but presents frequency information that the latter can not explain. The power of wavelets then enters the scene to reveal a small treasure hidden in the sound signal that Fourier's analysis could not bring to light.
Know moreKey points
Reliability and simplicity
- Analysis with wavelet frames
- Multigrid and super-resolution computations
- Fast wavelet algorithms
Optimization
Main stakes
Services
Letscan performs time-frequency analyses of complex signals to
- extract
- characterize
- understand
their essential components.
Letscan helps you to develop a scientific background and to build together a solution adapted to your expectations and stakes:
- simple question
- feasibility project
- R&D project
Letscan is at your disposal to provide you with more information about other applications of signal analysis with wavelet scalograms. Contact us without hesitation