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  2. Pan–Tompkins algorithm - Wikipedia

    en.wikipedia.org/wiki/Pan–Tompkins_algorithm

    In order to detect a QRS complex, the local peaks of the integrated signal are found. A peak is defined as the point in which the signal changes direction (from an increasing direction to a decreasing direction). After each peak, no peak can be detected in the next 200 ms (i.e. the lockout time).

  3. Hough transform - Wikipedia

    en.wikipedia.org/wiki/Hough_transform

    The Hough transform is a feature extraction technique used in image analysis, computer vision, pattern recognition, and digital image processing. [1] [2] The purpose of the technique is to find imperfect instances of objects within a certain class of shapes by a voting procedure.

  4. Circle Hough Transform - Wikipedia

    en.wikipedia.org/wiki/Circle_Hough_Transform

    The circle Hough Transform (CHT) is a basic feature extraction technique used in digital image processing for detecting circles in imperfect images. The circle candidates are produced by “voting” in the Hough parameter space and then selecting local maxima in an accumulator matrix.

  5. NeuroKit - Wikipedia

    en.wikipedia.org/wiki/NeuroKit

    It also implements a variety of different algorithms to detect R-peaks and other QRS waves, including an efficient in-house R-peak detector. [10] [11] For neurophysiological signals such as EEG, it supports microstates and frequency band analysis. [citation needed]

  6. Line detection - Wikipedia

    en.wikipedia.org/wiki/Line_detection

    The Hough transform [3] can be used to detect lines and the output is a parametric description of the lines in an image, for example ρ = r cos(θ) + c sin(θ). [1] If there is a line in a row and column based image space, it can be defined ρ, the distance from the origin to the line along a perpendicular to the line, and θ, the angle of the perpendicular projection from the origin to the ...

  7. Component detection algorithm - Wikipedia

    en.wikipedia.org/wiki/COmponent_Detection_Algorithm

    The component detection algorithm (CODA) is a name for a type of LC-MS [1] [2] and chemometrics [3] software algorithm focused on detecting peaks in noisy chromatograms (TIC) often obtained using the electrospray ionization technique. The implementation of the algorithm from one piece of mass spectrometry software to another differs. Some ...

  8. List of numerical libraries - Wikipedia

    en.wikipedia.org/wiki/List_of_numerical_libraries

    The analysis class libraries provide various digital signal processing, signal filtering, signal generation, peak detection, and other general mathematical functionality. ML.NET is a free software machine learning library for the C# programming language. [3] [4] The NAG Library has C# API. Commercially licensed.

  9. MUSIC (algorithm) - Wikipedia

    en.wikipedia.org/wiki/MUSIC_(algorithm)

    MUSIC outperforms simple methods such as picking peaks of DFT spectra in the presence of noise, when the number of components is known in advance, because it exploits knowledge of this number to ignore the noise in its final report.