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Unformatted text preview: EE380: Communication Systems Spring 2010-2011 Quantization Error and Quantization Noise (For a Uniform Quantizer) Consider a quantizer whose input signal is x ( t ) and the output is the quantized signal y ( t ). Then the quantization error q ( t ) = y ( t )- x ( t ). For a given sample, we define: q = Y- X . When the probability density function of X is smooth and the number of quantization intervals ( L ) is large, we will find an expression for quantization noise, i.e., power of q ( t ) without assuming that q is a uniform random variable. Let the density function of X is f X ( x ). We define p k as the probability that X lies between x k- 1 and x k (see figure). Note that x k- 1 and x k are the end points of the k-th quantization interval. Whenever X falls within this interval, the output of the quantizer is y k . The corresponding quanti- zation error is y k- X . Clearly, the proba- bility of this error occurring is p k ....
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This note was uploaded on 03/11/2012 for the course EE EE380 taught by Professor Z.u during the Spring '11 term at Lahore University of Management Sciences.
- Spring '11