MATLAB: RMSE between original and predicted values.

MATLABrmse model

Hi,

If I have thousand samples of my signal in a vector form like 1*1000, and I will predict my signal at each iteration that results into 1*1000 also. Then In this case, how will I find the RMSE of my model?

Many Thanks

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MATLAB: RMSE between two variables

‘RMSE’ of course means ‘root mean squared error’, or the square root of the mean of the squared error.

The simplest code for this is then:

V1 = rand(10,1);
V2 = rand(10,1);
RMSE = sqrt(mean((V1-V2).^2));

where the error is (V1-V2), and ‘.^2’ denotes element-wise squaring of the error (the difference between ‘V1’ and ‘V2’). The rest of the expression takes the mean of the squared differences, and sqrt takes the square root, completing the definition.

See: Array vs. Matrix Operations (link) and Vectorization (link) for more information.

MATLAB: How to obtain matrix components

You need to enclose the variables you are solving for in square brackets:

[EL,vlt,vtl,ET,GLT] = solve(y,[EL,vlt,vtl,ET,GLT]);

returning:

EL =
19
 
vlt =
-3/10
 
vtl =
10/3
 
ET =
1
 
GLT =
7/10

As desired.

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MATLAB: RMSE between two variables

MATLAB: How to obtain matrix components

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