gaussian | 易学教程

Gaussian elimination without result for acceleration

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问题 Good day, I'm working on a C library (for myself, code: https://github.com/BattlestarSC/matrixLibrary.git) to handle matrix functions. This is mostly a learning/practice activity. One of my challenges is to take the determinant of a matrix efficiently. As my current attempts have failed, I wanted to take a different approach. I was reading though this method from MIT docs: http://web.mit.edu/18.06/www/Spring17/Determinants.pdf and it made a lot of sense. The issue I'm having is how to get to

how to generate a gaussian distribution using mysql user-defined function

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问题 I like to use MySQL to do quantitative analysis and statistics. I would like to make a MySQL user-defined function of the form: sample_gaussian(mean, stdev) that returns a single randomized value sampled from a gaussian distribution having mean and standard deviation of the user-entered arguments. MySQL already has a function rand() that returns a random number, so I just need to know some pseudocode for constraining/transforming that value so that it falls into the right distribution. Any

How to do a Gaussian filtering in 3D

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问题 How do i do a gaussi smoothing in the 3th dimension? I have this detection pyramid, votes accumulated at four scales. Objects are found at each peak. I already smoothed each of them in 2d, and reading in my papers that i need to filter the third dimension with a \sigma = 1, which i havent tried before, i am not even sure what it means. I Figured out how to do it in Matlab, and need something simular in opencv/c++. Matlab Raw Values: Matlab Smoothen with M0 = smooth3(M0,'gaussian'); : 回答1:

Generate a random number in a Gaussian Range?

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问题 I want to use a random number generator that creates random numbers in a gaussian range where I can define the median by myself. I already asked a similar question here and now I'm using this code: class RandomGaussian { private static Random random = new Random(); private static bool haveNextNextGaussian; private static double nextNextGaussian; public static double gaussianInRange(double from, double mean, double to) { if (!(from < mean && mean < to)) throw new ArgumentOutOfRangeException();

C++: generate gaussian distribution

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I would like to know if in C++ standard libraries there is any gaussian distribution number generator, or if you have any code snippet to pass. Thanks in advance. The standard library does not. Boost.Random does, however. I'd use that if I were you. C++ Technical Report 1 adds support for random number generation. So if you're using a relatively recent compiler (visual c++ 2008 GCC 4.3), chances are that it is available out of the box. See here for sample usage of std::tr1::normal_distribution (and many more). The GNU Scientific Libraries has this feature. GSL - Gaussian Distribution Shafik

Creating a Gaussian Random Generator with a mean and standard deviation

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I am trying to create a one dimensional array and use a random number generator(Gaussian generator that generates a random number with means of 70 and a standard deviation of 10) to populate the array with at least 100 numbers between 0 and 100 inclusive. How would i go about doing this in C++ ? In C++11 this is relatively straight forward using the random header and std::normal_distribution ( live example ): #include <iostream> #include <iomanip> #include <string> #include <map> #include <random> int main() { std::random_device rd; std::mt19937 e2(rd()); std::normal_distribution<> dist(70, 10

By which measures should I set the size of my Gaussian filter in MATLAB?

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I'm trying to learn image processing using MATLAB and I have read about filters on images. By considering this code: gaussianFilter = fspecial('gaussian', [7, 7], 5) , this builds a Gaussian filter matrix of 7 rows and 7 columns, with standard deviation of 5. As such, the size of filter matrix is 7 x 7 . How can the size of this matrix be effective on filtering? (What does this matrix do ?) By which measures should I set the size of filter matrix in my code? One of the most common and heuristic measures on determining the size and ultimately the standard deviation of the Gaussian filter is

Python unsharp mask

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问题 I want to use unsharp mask on a 16 Bit Image. The Image has 640 x 480 Pixel and is saved in a numpy array. In the first Step i blur the Image withe a Gaussian filter (three different Methods). After this i create a Mask by subtract the blur Image form the Original. in The last step i add the Mask multiplied by wightfaktor to the Original Image. But it don´t really works. Here is the Python code: Gaussian1 = ndimage.filters.gaussian_filter(Image,sigma=10.0) Gaussian2 = filters.gaussian_filter

How to specify upper and lower limits when using numpy.random.normal

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IOK so I want to be able to pick values from a normal distribution that only ever fall between 0 and 1. In some cases I want to be able to basically just return a completely random distribution, and in other cases I want to return values that fall in the shape of a gaussian. At the moment I am using the following function: def blockedgauss(mu,sigma): while True: numb = random.gauss(mu,sigma) if (numb > 0 and numb < 1): break return numb It picks a value from a normal distribution, then discards it if it falls outside of the range 0 to 1, but I feel like there must be a better way of doing this

JavaScript Math.random Normal distribution (Gaussian bell curve)?

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I want to know if the JavaScript function Math.random uses a normal (vs. uniform) distribution or not. If not, how can I get numbers which use a normal distribution? I haven't found a clear answer on the Internet, for an algorithm to create random normally-distributed numbers. I want to rebuild a Schmidt-machine (German physicist). The machine produces random numbers of 0 or 1, and they have to be normally-distributed so that I can draw them as a Gaussian bell curve. For example, the random function produces 120 numbers (0 or 1) and the average (mean) of these summed values has to be near 60.