Interpolation and energy amplification

Consider the following interpolator [1]

where x_u = (\uparrow L) (x) is the upsampling of sequence x by an integer factor of L, and where H(z) is the transfer function of an ideal discrete-time LTI lowpass filter with gain L and cutoff frequency \pi/L. What is the relation between the energies of signals x and y?

__________

My solution:

It can be easily shown [1] that the interpolator’s input-output relationship is Y (z) = H(z) X (z^L). Hence, evaluating the Z-transforms on the unit circle, we obtain

Y (e^{j \omega}) = H(e^{j \omega}) X (e^{j \omega L}).

The energy of the interpolator’s output signal is

\mathcal{E}_y := \displaystyle \sum_{n \in \mathbb{Z}} | y(n) |^2 = \frac{1}{2 \pi} \int_{-\pi}^{\pi} |Y (e^{j \omega})|^2 d \omega

where we used Parseval’s theorem for discrete-time signals. Thus,

\mathcal{E}_y = \displaystyle\frac{1}{2 \pi} \int_{-\pi}^{\pi} |H(e^{j \omega})|^2 |X (e^{j \omega L})|^2 d \omega.

H(z) is an ideal lowpass filter with the following frequency response

H(e^{j \omega}) = \begin{cases} L, & |\omega| \leq \pi/L\\ 0, & \pi/ L< |\omega| \leq \pi\end{cases}

and the following sinc impulse response

h(n) = \displaystyle\frac{1}{2 \pi} \int_{-\pi}^{\pi} H(e^{j \omega}) e^{j \omega n} d \omega = \displaystyle \frac{\sin(\frac{n \pi}{L})}{\frac{n \pi}{L}} =: \text{sinc} \left(\frac{n \pi}{L}\right).

Please do note that this is a non-causal filter with an impulse response of infinite length. We can then write the interpolator’s output signal’s energy as follows

\mathcal{E}_y = \displaystyle\frac{1}{2 \pi} \int_{-\pi}^{\pi} |H(e^{j \omega})|^2 |X (e^{j \omega L})|^2 d \omega = \displaystyle\frac{L^2}{2 \pi} \int_{-\pi/L}^{\pi/L} |X (e^{j \omega L})|^2 d \omega.

Performing a change of variable, \theta = L \omega, we obtain

\mathcal{E}_y = \displaystyle\frac{L^2}{2 \pi} \int_{-\pi/L}^{\pi/L} |X (e^{j \omega  L})|^2 d \omega = \displaystyle\frac{L}{2 \pi} \int_{-\pi}^{\pi} |X (e^{j \theta})|^2 d \theta = L \mathcal{E}_x

where

\mathcal{E}_x := \displaystyle \sum_{n \in \mathbb{Z}} | x(n) |^2 = \frac{1}{2 \pi} \int_{-\pi}^{\pi} |X (e^{j \omega})|^2 d \omega

is the energy of the input signal. Since \mathcal{E}_y = L \mathcal{E}_x, we can conclude that the interpolator amplifies the input signal’s energy by a factor of L, which is somewhat intuitive.

We considered the case where signals are bi-infinite sequences and H(z) is a non-causal ideal lowpass filter. It would be interesting to consider the more realistic case where the signals are finite sequences and H(z) is a causal FIR filter.

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References

[1] Alan V. Oppenheim, Ronald W. Schafer, Discrete-Time Signal Processing, 2nd edition, Prentice-Hall, 1999.

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2 Responses to “Interpolation and energy amplification”

  1. eryksun Says:

    It’s inaccurate to call this energy amplification. When one calculates discrete-time energy, it’s in Watt·samples. The result only truly becomes a physical unit of energy after scaling by the sample time, i.e.

    \text{Watt} \times \text{samples} \times \displaystyle\frac{\text{seconds}}{\text{sample}} = \text{Watt} \times \text{seconds} = \text{Joules}.

    While there are L times as many Watt·samples, the sample time is also reduced by L. The gain of L on the low pass filter is there to compensate for the loss due to the expander (i.e. inserting zeros). It’s not amplification.

    • Rod Carvalho Says:

      As an EE, I understand your objection. Nonetheless I have to disagree. It is energy amplification because I defined energy as

      \mathcal{E}_x := \displaystyle \sum_{n \in \mathbb{Z}} | x(n) |^2.

      Nowhere did I claim that this energy was physical. Interpolation is part of Numerical Analysis, too. It’s wider than DSP. And not all sequences are obtained by sampling continuous-time signals.

      Having said that, your comment got me interested in the relation between the physical energies of the interpolator’s input and output.

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