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Difference Quantization

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Pasted image 20240312145037.png In this system we Set UnU_{n} to be an arbitrary RV with a finite second moment (i.e.Ā E[Un2]<āˆžE[U_{n}^{2}]<\infty). Since en=Xnāˆ’Une_{n}=X_{n}-U_{n} and e^n=X^nāˆ’Un\hat{e}_{n}=\hat{X}_{n}-U_{n} then we have that E[(Xnāˆ’X^n)2]=E[(Xnāˆ’Unāˆ’(X^nāˆ’Un))2]=E[(enāˆ’e^n)2]=E[(enāˆ’Q(en))2]\begin{align*} E[(X_{n}-\hat{X}_{n})^{2}]&=E[(X_{n}-U_{n}-(\hat{X}_{n}-U_{n}))^{2}]\\ &=E[(e_{n}-\hat{e}_{n})^{2}]\\ &=E[(e_{n}-Q(e_{n}))^{2}] \end{align*}Here we see the MSE of the reconstruction does not accumulate the error and is merely the MSE of the quantizer.

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