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    <p>It depends on the unit of your timeseries. Often we think of this as just "amplitude", but if your timeseries is a series of voltage amplitude vs. time, then your PSD estimate will be <code>Volts^2/Hz</code>. This is because the PSD is the Fourier Transform of the autocorrelation of your original signal: The autocorrelation has units of <code>Volts^2</code>, and running it through the Fourier Transform decomposes these units over frequency, instead of time, resulting in units of <code>Volts^2/Hz</code>. This is commonly referred to as <code>Watts/Hz</code>, but the conversion from <code>Volts^2</code> to <code>Watts</code> is not very physically meaningful, as <code>W = V^2/R</code>.</p> <p><code>10*log10(power)</code> will result in a unit of <code>dB/Hz</code>, but remember that decibels are always a comparison between two power levels; you are quantifying a ratio of powers. A better definition of decibels is <code>10*log10(P1/P0)</code>, <a href="http://en.wikipedia.org/wiki/Decibel#Power_quantities">as explained here</a>. If you simply plug a PSD bin estimate into this equation, you are setting your PSD bin to <code>P1</code> and implicitly comparing it to a <code>P0</code> value of 1. This may be what you want, and it may not be. For visualization purposes, this is fairly typical, but if you have a standard reference power you should be comparing to, you should use that for <code>P0</code> instead.</p> <p>Assuming that you are attempting to plot a dB Power Spectral Density estimate, to convert from <code>Hz</code> to <code>MHz</code>, you simple rescale the x-axis of your frequency graph. Remember that a MHz is just 1 million Hz, so the only difference is that <code>240000Hz</code> = <code>0.24MHz</code></p> <p><strong>EDIT</strong> The point brought up by mtrw is a very valid one; if you are dealing with large amounts of data and are averaging FFT vectors, I highly suggest the <a href="http://www.mathworks.com/help/signal/ref/pmtm.html">Multitaper method</a>; it's a much more statistically sound method of sacrificing frequency resolution for greater confidence on your PSD estimate.</p>
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    1. POwhat is the PSD unit by using FFT method
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