1. Trang chủ
  2. » Kỹ Thuật - Công Nghệ

Bài giảng Xử lý tín hiệu số: Chapter 2 - Hà Hoàng Kha

17 65 0

Đang tải... (xem toàn văn)

Tài liệu hạn chế xem trước, để xem đầy đủ mời bạn chọn Tải xuống

THÔNG TIN TÀI LIỆU

Thông tin cơ bản

Định dạng
Số trang 17
Dung lượng 467,43 KB

Nội dung

Bài giảng Xử lý tín hiệu số - Chapter 2: Quantization has contents: Quantization process, quantization error, digital to analog converters, A/D converter, A/D converter-example,...and other contents.

Chapter p Quantization Ha Hoang Kha, Ph.D.Click to edit Master subtitle style Ho Chi Minh City University of Technology @ Email: hhkha@hcmut.edu.vn CuuDuongThanCong.com https://fb.com/tailieudientucntt Quantization process Fig: Analog to digital conversion ™ The quantized sample xQ(nT) is represented by B bit, which can take 2B possible values values ™ An A/D is characterized by a full-scale range R which is divided into 2B quantization levels l l Typical T l values l off R in practice are between 1-10 volts Ha H Kha CuuDuongThanCong.com Quantization https://fb.com/tailieudientucntt Quantization process Fig: Signal quantization ™ Quantizer resolution or quantization width Q = ™ A bipolar bip l ADC − R R ≤ xQ (nT ) < 2 R 2B ™ A unipolar p ADC ≤ xQ (nT ) < R Ha H Kha CuuDuongThanCong.com Quantization https://fb.com/tailieudientucntt Quantization process –Quantization error ™ Quantization by rounding: replace each value x(nT) by the nearest q antization le quantization level el ™ Quantization by truncation: replace each value x(nT) by its below quantization level ™ Quantization error: e(nT ) = xQ (nT ) − x(nT ) ™ Consider rounding quantization: − Q Q ≤e≤ 2 Fig: i Uniform if probability b bili density d i off quantization i i error Ha H Kha CuuDuongThanCong.com Quantization https://fb.com/tailieudientucntt Quantization process –Quantization error ™ The mean value of quantization error e = Q /2 ∫ Q /2 ep (e) de = − Q /2 ∫ − Q /2 Q /2 e de =0 Q Q /2 Q ™ The mean mean-square square error (power) σ = e2 = ∫ e p(e)de = ∫ e de = Q 12 − Q /2 − Q /2 ™ Root-mean-square Root mean square (rms) error: erms = σ = e2 = Q 12 ™ R and Q are the ranges g of the signal g and quantization q noise,, then the signal to noise ratio (SNR) or dynamic range of the quantizer is defined as ⎛R⎞ SNR dB = 20 log10 ⎜ ⎟ = 20 log10 (2 B ) = B log10 (2) = B dB ⎝Q⎠ which is referred to as dB bit rule rule Ha H Kha CuuDuongThanCong.com Quantization https://fb.com/tailieudientucntt Quantization process –Example ™ In a digital audio application, the signal is sampled at a rate of 44 KHz andd each h sample l quantized d using an A/ A/D converter h having a full-scale range of 10 volts Determine the number of bits B if the rms quantinzation error mush be kept below 50 microvolts microvolts Then, Then determine the actual rms error and the bit rate in bits per second Ha H Kha CuuDuongThanCong.com Quantization https://fb.com/tailieudientucntt Digital to Analog Converters (DACs) ™ We begin with A/D converters, because they are used as the building blocks of successive s ccessi e approximation appro imation ADCs ADCs Fig: B-bit D/A converter ™ Vector B input bits : b=[b1, b2,…,bB] Note that bB is the least significant f bit b (LSB) while h l b1 is the h most significant f bit b (MSB) ™ For unipolar signal, xQ є [0, R); for bipolar xQ є [-R/2, R/2) Ha H Kha CuuDuongThanCong.com Quantization https://fb.com/tailieudientucntt DAC-Example DAC Circuit Rf ™ Full scale R=VREF, B=4 bit 2Rf 4Rf ∑I 8Rf MSB i xQ=Vout 16Rf bB b1 LSB -VREF Fig: DAC using binary weighted resistor ⎛ b1 b3 b2 b4 I V = + + + ⎜ ∑ REF ⎜ R R 8R 16 R f f f ⎝ f ⎞ ⎟⎟ ⎠ ⎛ b1 b2 b3 b4 ⎞ xQ = VOUT = ∑ I ⋅ R f = VREF ⎜ + + + ⎟ ⎝ 16 ⎠ xQ = R 2−4 ( b1 2−3 + b2 2−2 + b3 2−1 + b4 20 ) = Q ( b1 2−3 + b2 2−2 + b3 2−1 + b4 20 ) Ha H Kha CuuDuongThanCong.com Quantization https://fb.com/tailieudientucntt D/A Converters ™ Unipolar natural binary xQ = R(b1 2−1 + b2 2−2 + + bB 2− B ) = Qm where m is the integer whose binary representation is b=[b1, b2,…,bB] m = b1 B −1 + b2 B − + + bB 20 ™ Bipolar offset binary: obtained by shifting the xQ of unipolar natural binary converter by half-scale R/2: xQ = R(b1 2−1 + b2 2−2 + + bB 2− B ) − R R =Q Qm − 2 ™ Two’s complement code: obtained from the offset binary code by complementing l the h most significant f b bit, i.e., replacing l b1 by b b1 = − b1 xQ = R (b1 2−1 + b2 2−2 + + bB 2− B ) − Ha H Kha R CuuDuongThanCong.com Quantization https://fb.com/tailieudientucntt D/A Converters-Example ™ A 4-bit D/A converter has a full-scale R=10 volts Find the quantized analog l values l f the for h ffollowing ll cases ? a) Natural binary with the input bits b=[1001] ? b) Offset binary with the input bits b=[1011] ? c)) Two’s T ’ complement l binary bi with i h the h input i bits bi b=[1101] b [1101] ? Ha H Kha 10 CuuDuongThanCong.com Quantization https://fb.com/tailieudientucntt A/D converter ™ A/D converters quantize an analog value x so that is is represented b B bits b=[b1, b2,…,b by bB].] Fig: B-bit A/D converter Ha H Kha 11 CuuDuongThanCong.com Quantization https://fb.com/tailieudientucntt A/D converter ™ One of the most popular converters is the successive approximation A/D converter erter Fig: Successive approximation A/D converter ™ After B tests, the successive approximation register (SAR) will hold the correct bit vector b Ha H Kha 12 CuuDuongThanCong.com Quantization https://fb.com/tailieudientucntt A/D converter ™ Successive approximation algorithm ⎧1 if x ≥ where the unit-step function is defined by u ( x) = ⎨ ⎩0 if x < This algorithm is applied for the natural and offset binary with quantization truncation q Ha H Kha 13 CuuDuongThanCong.com Quantization https://fb.com/tailieudientucntt A/D converter-Example ™ Consider a 4-bit ADC with the full-scale R=10 volts Using the s ccessi e approximation successive appro imation algorithm to find offset binary binar of truncation quantization for the analog values x=3.5 volts and x=-1.5 v volts Ha H Kha 14 CuuDuongThanCong.com Quantization https://fb.com/tailieudientucntt A/D converter ™ For rounding quantization, we shift x b by Q/2 Q/2: Ha H Kha ™ For the two’s complement code the sign bit b1 is treated code, separately 15 CuuDuongThanCong.com Quantization https://fb.com/tailieudientucntt A/D converter-Example ™ Consider a 4-bit ADC with the full-scale R=10 volts Using the s ccessi e approximation successive appro imation algorithm to find offset and two’s t o’s complement of rounding quantization for the analog values x=3.5 vvolts Ha H Kha 16 CuuDuongThanCong.com Quantization https://fb.com/tailieudientucntt Homework ™ Problems 2.1, 2.2, 2.3, 2.5, 2.6 Ha H Kha 17 CuuDuongThanCong.com Quantization https://fb.com/tailieudientucntt ... error e = Q /2 ∫ Q /2 ep (e) de = − Q /2 ∫ − Q /2 Q /2 e de =0 Q Q /2 Q ™ The mean mean-square square error (power) σ = e2 = ∫ e p(e)de = ∫ e de = Q 12 − Q /2 − Q /2 ™ Root-mean-square Root mean... b3 b2 b4 I V = + + + ⎜ ∑ REF ⎜ R R 8R 16 R f f f ⎝ f ⎞ ⎟⎟ ⎠ ⎛ b1 b2 b3 b4 ⎞ xQ = VOUT = ∑ I ⋅ R f = VREF ⎜ + + + ⎟ ⎝ 16 ⎠ xQ = R 2 4 ( b1 2 3 + b2 2 2 + b3 2 1 + b4 20 ) = Q ( b1 2 3 + b2 2 2 +... b=[b1, b2,…,bB] m = b1 B −1 + b2 B − + + bB 20 ™ Bipolar offset binary: obtained by shifting the xQ of unipolar natural binary converter by half-scale R /2: xQ = R(b1 2 1 + b2 2 2 + + bB 2 B )

Ngày đăng: 13/01/2020, 02:59

TỪ KHÓA LIÊN QUAN