4/13/2024 0 Comments Matlab decibel scaleOnce you plot the pattern just change the scale in matlab plot as 0 to -40. Once done now you can plot this normalised radiation pattern data using POLAR command and since you already have angles in radians so just directly use that. Now look for any negative values in gain column and replace it to 'Zero'. This make the highest gain of your result which is 6 dB in our example to 40 dB and other decreases accordingly.ģ. Now to make a plot with scale 0 to -40 dB which is most common, add 40-6 i.e 34 to all the gain. gain value for particular angle, say for example its 6 dB. Numerical Analysis Using MATLAB and Excel. yscale (ax, ) sets the scale for the specified axes object. We can use the semilogx(x,y) command that is similar to the plot(x,y). For example, yscale log is equivalent to yscale ('log'). You can also omit the parentheses and quotation marks when using this syntax. So to plot the normalised radiation patterns :Ģ. yscale (scale) sets the scale of the y -axis to be linear or logarithmic in the current axes. Other important thing to keep in mind is the POLAR function in matlab do not plot the negative gains and returns you with an error so you have to keep everything positive or zero values. max gain is '0' and then it decreases so the scale look likes 0,-5,-10. Excerpts and links may be used, provided that full and clear credit is given to Waqas Akram with appropriate and specific direction to the original content.Plotting radiation patterns in matlab is simple but little tricky. 3.6.2 The Decibel Scale In the SI units used by electrical engineers, the unit of power is the Watt. Unauthorized use and/or duplication of this material without express and written permission from this blog’s author and owner is strictly prohibited. In the computerized world of today (or when no one brings a calculator to the lab), these mental shortcuts can be very useful as a quick sanity check.Ĭopyright © 2008 – 2012 Waqas Akram. Alternatively, we can use 30 dB = (40 – 10) dB, which converts to (100 ÷ 3) = 33.3 (the magnitude of the approximation error is about the same as that of the first answer)
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