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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.
Perform the convolution of following sequences (a) x[n] = [1 2 3], N1 = 1 and h[n] = [1 - 1], N2 = 1 (b) x[n] = [1 2 3], N1 = 2 and h[n] = [1 - 1], N2 = 1 (c) x[n] = [1 2 3], N1 =
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 th
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