7) Suppose we have a message signal that is a sinusoid and we quantize it using a quantizer of L levels. Assuming that the quantization error for each sample is uniformly distributed in the interval , determine the signal to quantization noise ratio (SNR) in terms of L. Determine the SNR in terms of L if the message is changed to a triangular wave, again assuming that the errors are uniformly distributed.
7) Suppose we have a message signal that is a sinusoid and we quantize it using a quantizer of L levels. Assuming that the quantization error for each sample is uniformly distributed in the interval , determine the signal to quantization noise ratio (SNR) in terms of L. Determine the SNR in terms of L if the message is changed to a triangular wave, again assuming that the errors are uniformly distributed.
Introductory Circuit Analysis (13th Edition)
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ISBN:9780133923605
Author:Robert L. Boylestad
Publisher:Robert L. Boylestad
Chapter1: Introduction
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Quantization and Resolution
Quantization is a methodology of carrying out signal modulation by the process of mapping input values from an infinitely long set of continuous values to a smaller set of finite values. Quantization forms the basic algorithm for lossy compression algorithms and represents a given analog signal into digital signals. In other words, these algorithms form the base of an analog-to-digital converter. Devices that process the algorithm of quantization are known as a quantizer. These devices aid in rounding off (approximation) the errors of an input function called the quantized value.
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Transcribed Image Text:7) Suppose we have a message signal that is a sinusoid and we quantize it using a quantizer of L
levels. Assuming that the quantization error for each sample is uniformly distributed in the
interval , determine the signal to quantization noise ratio (SNR) in terms of L. Determine
the SNR in terms of L if the message is changed to a triangular wave, again assuming that the
errors are uniformly distributed.
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