Out of these two methods, which one is computationally intensive and why?
2 visualizaciones (últimos 30 días)
Mostrar comentarios más antiguos
Syed Haider
el 25 de Dic. de 2017
Comentada: Walter Roberson
el 26 de Dic. de 2017
I have a signal, let's say A6. It has 300 sample points. There are two different methods to estimate the magnitude of the signal. I want to know which method is computationally intensive.
The steps of the first method are as followed,
Step1: A = A6 - mean(A6);
Step2: B = A .* A;
Step3: C = cumsum(B);
Step4: D = trapz(C);
D represents the magnitude of the signal in terms of area under the curve.
The steps of the second method are as followed,
Step1: A = A6 .* A6;
Step2: B = cumsum(A);
Step3: Mean Square Error (MSE) between B and fitted straight line.
The value of the MSE represents the magnitude of the signal.
Thanks,
Irtaza
2 comentarios
Respuesta aceptada
Walter Roberson
el 25 de Dic. de 2017
trapz should have a lower constant of proportion because it is sum(C) - (C(1)+C(end)) /2 whereas mse requires sqrt(sum((C-B).^2)). Both are linear in size but one requires squaring as well as sum.
2 comentarios
Walter Roberson
el 26 de Dic. de 2017
Unless you have a formula for the curve, there would be no way to calculate the area without examining each value at least once, which is all that trapz requires.
Más respuestas (0)
Ver también
Categorías
Más información sobre Numerical Integration and Differentiation en Help Center y File Exchange.
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!