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Lecture 7: Signal Processing IV. EEN 112: Introduction to Electrical and Computer Engineering. Professor Eric Rozier, 2/ 27/ 13. SCHEDULE. Schedule. QUANTIZATION. Recall the types of functions. Surjective. Injective. Classification and Reconstruction. 0 0.1 0.15762 0.2 0.333333
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Lecture 7: Signal Processing IV EEN 112: Introduction to Electrical and Computer Engineering Professor Eric Rozier, 2/27/13
Recall the types of functions Surjective Injective
Classification and Reconstruction 0 0.1 0.15762 0.2 0.333333 0.447 0.666666 0.9 1.0 0 0.1 0.15762 0.2 0.333333 0.447 0.666666 0.9 1.0 00 (0) 01 (1) 10 (2) 11 (3)
Classification and Reconstruction 0 0.1 0.15762 0.2 0.333333 0.447 0.666666 0.9 1.0 0 0.1 0.15762 0.2 0.333333 0.447 0.666666 0.9 1.0 00 (0) 01 (1) 10 (2) 11 (3)
Classification and Reconstruction 0 0.1 0.15762 0.2 0.333333 0.447 0.666666 0.9 1.0 0 0.1 0.15762 0.2 0.333333 0.447 0.666666 0.9 1.0 00 (0) 01 (1) 10 (2) 11 (3)
Classification and Reconstruction 0 0.1 0.15762 0.2 0.333333 0.447 0.666666 0.9 1.0 0 0.1 0.15762 0.2 0.333333 0.447 0.666666 0.9 1.0 00 (0) 01 (1) 10 (2) 11 (3)
Classification and Reconstruction 0 0.1 0.15762 0.2 0.333333 0.447 0.666666 0.9 1.0 0 0.1 0.15762 0.2 0.333333 0.447 0.666666 0.9 1.0 00 (0) 01 (1) 10 (2) 11 (3)
Classification and Reconstruction 0 0.1 0.15762 0.2 0.333333 0.447 0.666666 0.9 1.0 0 0.1 0.15762 0.2 0.333333 0.447 0.666666 0.9 1.0 00 (0) 01 (1) 10 (2) 11 (3)
Classification and Reconstruction 0 0.1 0.15762 0.2 0.333333 0.447 0.666666 0.9 1.0 0 0.1 0.15762 0.2 0.333333 0.447 0.666666 0.9 1.0 00 (0) 01 (1) 10 (2) 11 (3)
Classification and Reconstruction 0 0.1 0.15762 0.2 0.333333 0.447 0.666666 0.9 1.0 0 0.1 0.15762 0.2 0.333333 0.447 0.666666 0.9 1.0 00 (0) 01 (1) 10 (2) 11 (3)
Classification and Reconstruction 0 0.1 0.15762 0.2 0.333333 0.447 0.666666 0.9 1.0 0 0.1 0.15762 0.2 0.333333 0.447 0.666666 0.9 1.0 00 (0) 01 (1) 10 (2) 11 (3)
Quantization Error • Sampling is error free when we follow the Nyquist • Quantization always has some error.
Quantization Error • Let’s look at the error of quantizing the numbers 1-100 using various numbers of bits…
3-bit Quantization 99/7 = 14.1429…
4-bit Quantization 99/15= 6.6
5-bit Quantization 99/31 = 3.194…
6-bit Quantization 99/63 = 1.571…
Quantization Error • The error introduced when reconstructing a signal • Given an N-bit quantization over a range, [a,b], what is the maximum error? Hint, think in terms of
Linear vs. Non-linear Quantization • So far we’ve dealt with linear quantization • There are other ways we might quantize data
Non-linear Quantization • How should we change our classifier and our reconstruction rule? • Hint: