Lecture2 - Interfacing a Microprocessor to the Analog World...

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Interfacing a Microprocessor to the Analog World In many systems, the embedded processor must interface to the non-digital, analog world. The issues involved in such interfacing are complex, and go well beyond simple A/D and D/A conversion. A/D CPU D/A ? ? Two questions: 1. How do we represent information about the analog world in a digital microprocessor? 2. How do we use a microprocessor to act on the analog world? We shall explore each of these questions in detail, both conceptually in the lectures, and practically in the laboratory exercises. EECS461, Lecture 2, updated September 6, 2007 1
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Sensors Used to measure physical quantities such as - position - velocity - temperature - sound - light Two basic types: - sensors that measure an (analog) physical quantity and generate an analog signal, such as a voltage or current A/D sensor physical quantity analog voltage digital * tachometer * potentiometer - sensors that directly generate a digital value sensor physical quantity digital * digital camera * position encoders EECS461, Lecture 2, updated September 6, 2007 2
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Sensor Interfacing Issues Shall focus on issues that involve - loss of information - distortion of information Such issues include - quantization - sampling - noise Fundamental difference between quantization and sampling errors: - Quantization errors affect the precision with which we can represent a single analog value in digital form. - Sampling errors affect how well we can represent an entire analog waveform (or time function) digitally. EECS461, Lecture 2, updated September 6, 2007 3
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Quantization Digital representation of an analog number [2, 3, 6] Issue: - an analog voltage can take a continuum of values - a binary number can take only finitely many values Binary representation of (unsigned or signed) real number - unipolar coding - unipolar coding with centering - offset binary coding - two’s complement Resolution [2, 3] - Idea: two analog numbers whose values differ by < 1 / 2 n may yield the same digital representation - an n -bit A/D converter has a resolution equal to 2 n times the input voltage range, v [0 , V max ] - least significant bit (LSB) represents V max / 2 n EECS461, Lecture 2, updated September 6, 2007 4
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Quantization: Example Suppose we quantize an analog voltage in the range (0 , V max ) using a two bit binary number. The LSB thus represents V max / 4 0 V max 3V max 4 V max 2 V max 4 input voltage 00 01 10 11 Quantization error: from 0 to 1 LSB (e.g., 01 represents any voltage from V max / 4 to V max / 2 ) For 11 to uniquely represent V max , divide voltage range into 2 n 1 intervals. LSB = V max / (2 n 1) Centering: 01 represents V max / 8 to 3 V max / 8 0 V max 3V max 4 V max 2 V max 4 input voltage 00 01 10 11 Quantization error: ± 1 2 LSB EECS461, Lecture 2, updated September 6, 2007 5
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A/D Conversion A/D analog voltage n-bit binary number Types of A/D converters [2]: - flash - successive approximation (MPC555) - single-slope (or dual-slope) integration - sigma-delta converters - redundant signed digit (RSD) [5] (MPC5553) Design issues - precision - accuracy - speed - cost
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