err = immse(X, Y) calculates the mean-squared error (MSE) between the arrays X and Y. X and Y can be arrays of any dimension, but must be of the same size. What you have written is different, in that you have divided by dates, effectively normalizing the result. Also, there is no mean, only a sum. The difference is that a . This MATLAB function takes a matrix or cell array of matrices and returns, Sum of all squared finite values Number of finite values.

What you have written is different, in that you have divided by dates, effectively normalizing the result. Also, there is no mean, only a sum. The difference is that a . symbolic toolbox is not the usual way to do least square method in MATLAB, the most used p = @(x)*x S = sum((p(xi)-yi).^2,2. According to the distributive property in mathematics you forgot the brackets. I shortened your code a little with (:) - which creates a column vector in any case. How do we computer SSD (Sum of Squared Learn more about image processing, digital image processing, image analysis Image Processing Toolbox. err = immse(X, Y) calculates the mean-squared error (MSE) between the arrays X and Y. X and Y can be arrays of any dimension, but must be of the same size. I am having two images I and J. How can found distance between this two images with using SSd? mean squared error. If I1 and I2 are uint numbers, you'll have to cast to double to avoid clipping. This MATLAB function takes a matrix or cell array of matrices and returns, Sum of all squared finite values Number of finite values. If one temporarily ignores the constraint that v be a non-negative integer, this is a linear least squares problem in disguise and therefore has an. Calculate Sum of Square Error. Learn more about linear regression.

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