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two-dimensional convolution with a 50-point gaussian distribution window  (MathWorks Inc)


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    MathWorks Inc two-dimensional convolution with a 50-point gaussian distribution window
    Two Dimensional Convolution With A 50 Point Gaussian Distribution Window, 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/two+dimensional+convolution/pmc03457078-90-10-18
    Average 90 stars, based on 1 article reviews
    two-dimensional convolution with a 50-point gaussian distribution window - by Bioz Stars, 2026-10
    90/100 stars

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    Article Title: Tray inserts and image quality, systems, methods and algorithm for quantifying tray's impact using the same
    Article Snippet: This type of calculation is typically achieved with a linear convolution of two one-dimensional sequences (e.g. cony in MATLAB or numpy.convolve in Python).

    Article Title: Coordinate-targeted fluorescence nanoscopy with multiple off states
    Article Snippet: Far-field super-resolution fluorescence microscopy discerns fluorophores residing closer than the diffraction barrier by briefly transferring them in different (typically ON and OFF) states before detection.. In coordinate-targeted superresolution variants, such as stimulated emission depletion (STED) microscopy, this state difference is created by the intensity minima and maxima of an optical pattern, causing all fluorophores to assume the off state, for instance, except at the minima.. Although strong spatial confinement of the on state enables high resolution, it also subjects the fluorophores to excess intensities and state cycles at the maxima.

    Article Title: Quantification of Sub-Pixel Dynamics in High-Speed Neutron Imaging
    Article Snippet: In effect, Equation (15) computes the integral of the product of two functions as one is shifted past the other, which is equivalent to convolution: (16) E [ d ( x , a ) ] = f a ( x ) * d ( x ) = ∫ − ∞ ∞ f a ( β ) d ( x − β ) d β This was implemented by performing discrete convolution over a finite domain in MATLAB [ ].

    Article Title: Probabilistic volumetric speckle suppression in OCT using deep learning
    Article Snippet: In the original version TNode2018, this compounded probability is computed via convolution with a kernel using MATLAB’s built-in function.

    Article Title: A Physiologically Inspired Model for Solving the Cocktail Party Problem
    Article Snippet: The estimated stimulus is obtained via a two-dimensional convolution obtained without zero-padding (“valid” mode in MATLAB or Python): s est , f = h f ( t , ω ) ∗ x ( t , ω ), where x ( t , ω ) is the response spike trains for all frequency channels over time t . Since the convolution is only computed on elements that do not require zero-padding, the result is a one-dimensional signal of length (t–2048).

    Article Title: Generating Artificial Reverberation via Genetic Algorithms for Real-Time Applications
    Article Snippet: For real-time convolution reverb, an object that performs partitioned fast convolution is readily available in Matlab [ ].

    Activity Assay:

    Article Title: A Method for Point Spread Function Estimation for Accurate Quantitative Imaging
    Article Snippet: Aim: A method to determine the point spread function (PSF) of an imaging system based on a set of 3-D Gaussian functions is presented for a robust estimation of the recovery corrections for accurate activity quantification in positron emission tomography (PET) and single-photon emission computed tomography systems.. Materials and Methods: The spatial resolution of the ALBIRA II PET subsystem was determined using a 370-kBq 22Na point source.. The measured data were reconstructed with a maximum-likelihood expectationmaximization algorithm.

    Sequencing:

    Article Title: SACT: A New Model of Covert Communication Based on SDN
    Article Snippet: The output sequences of each output end after passing through the encoder are as follows: O 1 = G 1 ∗ s = 101110001 ∗ 110110 = 100110111010110 O 2 = G 2 ∗ s = 111101011 ∗ 110110 = 110011110010010 After combining the output sequences of O 1 and O 2 , the resulting of extended sequence is as follows: ( 11 , 01 , 00 , 10 , 11 , 01 , 11 , 11 , 10 , 00 , 11 , 00 , 10 , 11 , 00 ) The convolution operation of vector can be realized by c o n vfunction in MATLAB. .. Therefore, the implementation of convolution coding in MATLAB are as follows: (6) O 1 = m o d c o n v s , G 1 , 2 O 2 = m o d c o n v s , G 2 , 2 Then the m file program is compiled into j a r package to encode the watermark information sequence. ..



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