Quantization - week 6
- Created by: harveyf2801
- Created on: 13-01-21 21:54
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- Quantisation
- Approximates a signal amplitude for each sample and creates discrete digital representations
- Problems with quantisation
- Quantization rounding error
- To reduce this the bit depth can be increased
- These errors result in noise
- The signal to noise ratio (SNR) can be calculated by SNR = 6.02n + 1.76dB
- These errors result in noise
- To reduce this the bit depth can be increased
- Analogue voltage exceeds maximum quantization level
- The maximum analogue value that can be represented is called full scale deflection (FSD)
- Quantization rounding error
- The digital representation is in binary (base 2)
- The leftmost digit is the most significant bit (MSB)
- The rightmost digit is the least significant bit (LSB)
- The dynamic range is the ration from the largest to smallest amplitudes in the signal
- Dynamic range = 20 log(2^n - 1)
- The number of levels that can be represented in an ADC circuit
- 2^n - 1
- n = bit depth
- Before quantization the signal is first sampled
- Sampling period: the time between successive samples
- Sampling period = 1 / sampling frequency
- Sampling frequency: how many times the signal is sampled per second
- Sampling period: the time between successive samples
- Sampling period: the time between successive samples
- Sampling period = 1 / sampling frequency
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