Y = RMS(X) Y = RMS(X,DIM) Explanation: Y = RMS(X) returns the root-mean-square (
ID: 2247453 • Letter: Y
Question
Y = RMS(X)
Y = RMS(X,DIM)
Explanation:
Y = RMS(X) returns the root-mean-square (RMS) level of the input, X. If X is a row or column vector, Y is a real-valued scalar. For matrices, Y contains the RMS levels computed along the first nonsingleton dimension. For example, if X is an N-by-M matrix with N > 1, Y is a 1-by-M row vector containing the RMS levels of the columns of X.
Y = RMS(X,DIM) computes the RMS level of X along the dimension, DIM.
Or simply use this also:
RMSE = sqrt(mean((y-y_pred).^2));
Or easy to approach:
r = sqrt( sum( (data(:)-estimate(:)).^2) / numel(data) );
for question #4 i just need help to write the new code in matlab
Run for sequence of 5 spring constant K (all other parameters remain the same. If the spring constant from part (1) is k_0 then the sequence of spring constant in k_0/100, k_0/10, 10k_0, 100 k_0. Discuss your result, and conclude relationship between K and results.Explanation / Answer
RMS
Root-mean-square leve
Sentence structure
Y = rms(X)
Y = rms(X,DIM)
Portrayal
Y = rms(X) restores the root-mean-square (RMS) level of the information, X. On the off chance that X is a line or section vector, Y is a genuine esteemed scalar. For lattices, Y contains the RMS levels processed along the primary nonsingleton measurement. For instance, if X is a N-by-M framework with N > 1, Y is a 1-by-M push vector containing the RMS levels of the segments of X.
Y = rms(X,DIM) registers the RMS level of X along the measurement, DIM.
Information Arguments
X Real or complex-esteemed information vector or network. Of course, rms acts along the primary nonsingleton measurement of X.
DIM Dimension for RMS levels. The discretionary DIM information contention indicates the measurement along which to register the RMS levels.
Default: First nonsingleton measurement
Yield Arguments
Y Root-mean-square level. For vectors, Y is a genuine esteemed scalar. For frameworks, Y contains the RMS levels registered along the predetermined
measurement DIM. As a matter of course, DIM is the primary nonsingleton measurement.
Illustrations
RMS Level of Sinusoid
Figure the RMS level of a 100 Hz sinusoid inspected at 1 kHz.
t = 0:0.001:1-0.001;
x = cos(2*pi*100*t);
y = rms(x)
y =
0.7071
RMS Level of 2-D Matrix
Figure the RMS level of a 100 Hz sinusoid inspected at 1 kHz.
t = 0:0.001:1-0.001;
x = cos(2*pi*100*t);
y = rms(x)
y =
0.7071 1.4142 2.1213 2.8284
RMS Level of 2-D Matrix Along Specified Dimension
Make a lattice where each column is a 100 Hz sinusoid inspected at 1 kHz with an alternate abundancy. The abundancy is equivalent to the line record.
Register the RMS levels of the lines indicating the measurement equivalent to 2 with the DIM contention.
t = 0:0.001:1-0.001;
x = (1:4)'*cos(2*pi*100*t);
y = rms(x,2)
y =
0.7071
1.4142
2.1213
2.8284
Related Questions
Navigate
Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.