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peak finder algorithm  (MathWorks Inc)


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    MathWorks Inc peak finder algorithm
    Peak Finder Algorithm, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/peak+finder+algorithm/pm37766975-326-7-13
    Average 90 stars, based on 1 article reviews
    peak finder algorithm - by Bioz Stars, 2026-09
    90/100 stars

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    Article Title: Silicon Nitride Photonic Particle Detector—Experiments and Model Assessment
    Article Snippet: Multi mode fiber Abstract— Sensors based on the interaction between analytes and the evanescent field of a silicon nitride waveguide are emerging in the field of bio-medical and environmental applications.. We designed and implemented the first single particle detector based on this sensor principle that consists of a silicon nitride waveguide with sub-micron dimensions.. The detection capabilities of the prototype were demonstrated with polystyrene latex (PSL) spheres equal to or greater than Ø 200 nm.

    Article Title: Measurement of exhaled volatile organic compounds from patients with chronic obstructive pulmonary disease (COPD) using closed gas loop GC-IMS and GC-APCI-MS.
    Article Snippet: In the second step of the univariate analysis, peaks were determined using a peak finder algorithm written in MATLAB.

    Article Title: Method and system for dereverberation of signals propagating in reverberative environments
    Article Snippet: The Prominent Features Finder 46 may apply a number of algorithms, such as, for example: (a) Repeated gradient ascent algorithm; (b) Stochastic region contraction algorithm; (c) Mean-shift algorithm; (d) Peak finder algorithm built into the MATLAB software; (e) Specialized parallel hardware implementation; as well as many others.

    Article Title: Effect of Adjusting Retinal Nerve Fiber Layer Profile to Fovea-Disc Angle Axis on the Thickness and Glaucoma Diagnostic Performance.
    Article Snippet: PURPOSE: To compare optical coherence tomography (OCT) retinal nerve fiber layer (RNFL) thickness, specificity, and glaucoma discriminating ability prior and following adjustment to the fovea-disc angle axis.. DESIGN: Cross-sectional observational study.. METHODS: Fovea-disc angle was measured in 282 healthy subjects (normative database), 46 nonglaucomatous myopic subjects, and 86 glaucomatous subjects.

    Article Title: Detecting Gait Events from Accelerations Using Reservoir Computing
    Article Snippet: This could be related to our implementation in the Python programming language, where the peak finder algorithm [ ] was different compared to the one used in the original MATLAB implementation [ ].

    Standard Deviation:

    Article Title: Immediate responses to ambient light in vivo reveal distinct subpopulations of suprachiasmatic VIP neurons
    Article Snippet: .. The event rate was calculated using the peak finder algorithm (“findpeaks” using “Annotate,” Matlab), with a threshold of one standard deviation above the mean value in the baseline period. .. To quantify the response intensity vs. the distance between the target (SCN) and the fiber tip , we first defined the response intensity as the width x prominence (“findpeaks”, Matlab, as above).

    Article Title: Immediate responses to ambient light in vivo reveal distinct subpopulations of suprachiasmatic VIP neurons.
    Article Snippet: .. The event rate was calculated using the peak finder algorithm (‘‘findpeaks’’ using ‘‘Annotate,’’ Matlab), with a threshold of one standard deviation above the mean value in the baseline period. .. To quantify the response intensity vs. the distance between the target (SCN) and the fiber tip (Figure S2), we first defined the response intensity as thewidth x prominence (‘‘findpeaks’’, Matlab, as above).



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