m m color distribution

#1, principleEach picture can generate a histogram of color distributions (histogram). If the histogram of the two pictures is close enough, you can think of them as similar.Any one color is made up of red, green, and Blue (RGB), so there are 4 histogram (the histogram of the primary color + the last synthesized straight-side graph).If you can take 256 values for

1, what is the index distribution family 1.1 basic descriptionExponential distribution is a kind of important distribution family, in statistical inference, exponential distribution family occupies an important position, which is widely used in various fields. Many of the statistical distributions are exponential

Distribution system to help traditional micro-business transformation of the Internet, quickly set up their own sales platform for micro-commerce, mobile distribution of the first weapon, distribution system built-in fission marketing program, promotional plug-in to achieve multi-channel sales of enterprise products, more people to participate in marketing togeth

Knowledge Points: Bernoulli distribution, two-item distribution, polynomial distribution, prior probability, posterior probability, conjugate distribution, beta distribution, beta-two-item distribution, negative two-item

Multinomial distribution The corresponding multivariate distribution can be obtained by extending the two-yuan case of two-yuan distribution to multiple variables. First, the Bernoulli distribution is extended to the multivariate hypothesis for the discrete variable x x, there may be K K, then x x observation is repres

http://blog.csdn.net/shuimu12345678/article/details/307739290-1 Distribution:In one experiment, either 0 or 1 distribution, called 0-1 distribution.Two items distributed:To do the N-1-p experiment, the probability of 1 for each experiment was p, the probability of the experiment being 0 was, the probability that there was K for 1,n-k Times was 0, two distribution B (N,p,k).Two-Item

"Fitting of distribution" The distribution function of the sample (also known as the "Experiential distribution function") is stacked with the distribution function of a theory (such as the normal distribution) to be compared.For example: Score = Xlsread (' Examp02_14.xls ',

the sampling average: Among them, is the sampling average. This example shows that the finite variable hypothesis in the central limit theorem cannot be discarded.Lorentz linear distribution is more suitable for the relatively flat, wide curve Gaussian linear distribution is suitable for a higher, narrower curve of course, if it is a more centered situation, both can. In many cases, the use o

% 0.04 5. Complete the histogram of frequency distribution Hold down "Ctrl" and select "group", "", and "cumulative frequency" from top to bottom in the above distribution table, click "chart wizard" in the Excel toolbar, select a column chart type, select a column chart type for ink recognition, and click "Next" twice in a row, enter the corresponding information in the chart title, X axis, and Y

"group", "", and "cumulative frequency" from top to bottom in the above distribution table, click "chart wizard" in the Excel toolbar, select a column chart type, select a column chart type for ink recognition, and click "Next" twice in a row, enter the corresponding information in the chart title, X axis, and Y axis dialog box under the title and click "finish" to obtain the following frequency (cumulative) dist