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Temperature readings were done every hour (starting at 1 P.M., but the end time could vary) and stored in a vector called readings. Write a function called halffit that receives this vector as an argument and uses a quadratic interpolation (second order) to determine what the temperature was every half hour between the actual recorded temperatures.
The function then plots, on one graph, the original temperature readings (using a ‘o' for the points), the interpolated temperatures at the half hours (using a '+' for these points), and the quadratic curve that was used for the interpolation. Put a legend on the graph to distinguish them. The number of hours that was used for the original vector may not be assumed. For example, the function might be called as follows:
>>readings = [33, 40, 42, 41, 39, 32];>>halffit(readings)
The Figure Window would look like the following.
The average speed of vehicles on a freeway is being studied. Assume that the standard deviation of vehicle speed is known to be 8 km/h. (a) Suppose observations on 120 vehicles
Linear indexing: This is termed as linear indexing. It is generally much better style when working with the matrices to refer to the row and column indices, although. An in
Adaptive filters can also be used in other applications. Speech recognition, for example, is performed in a non-stationary environment, and therefore may require adaptive filtering
how can i model this eqn: solve n plot x vs v x^3-2x^2+x=v^2(.532*10^-3) by putting v=0 to 20 and find the change in x
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write matlab program for Cubic Spline Sweep Surface
(a) Using Matlab, find and plot the magnitude of the DTFT of 10 samples of x(n) for n=[0:1:9] of x(n) = cos(2*pi*f1*n) + cos(2*pi*f2*n) for f1=0.22 and f2=0.24 and pad zeros to ge
A 300 km, 3-phase, 50Hz transmission line has spacing as shown in Figure 2. Each phase of the line consists of a bundle of three conductors. (a) Find the total per-phase induct
Solve the optimality condition for each P equation against M according to the following relation: Condition for Optimality: ∇ M = λ ∇ P with respect to C and T.
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