ECE
Lec22FloatingPoint

# Lec22FloatingPoint - Lecture 22 Math Calculation Using...

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ECE 471 22-1 Outline Data representation Fixed Point Math Binary Factions Discussion and Summary Lecture 22: Math Calculation Using Fixed Point Processors

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ECE 471 22-2 Floating point Number Representation Data objects of type float and double are represented as described in the IEEE floating point standard. Four bytes for a float Mantissa 30 23 22 0 Sign 31 Exponent
ECE 471 22-3 Data Representation IEEE floating point standard Eight bytes for a double Mantissa 62 52 51 0 Sign 63 Exponent

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ECE 471 22-4 Fixed Point Math Fixed point math is best used when: Float is slow Float uses too much memory Integer resolution is not sufficient More accurate representation of some fractions ANSI C does not have built-in support for Fixed Point Math Can be implemented as library routines Macros
ECE 471 22-5 Fixed Point Math The decimal point does not “float” Fixed number of digits to the right of the decimal point Program code is responsible for managing the decimal digits Range of values are limited Faster Use integer instructions for perform the operations Uses less memory No floating point libraries needed.

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ECE 471 22-6 Fixed Point Math Fixed point math is common in applications that must process data in real-time DSP ICs generally provide integral support for fixed point math FFT Digital filtering Process control Speech synthesis Voice recognition
ECE 471 22-7 Simple Example Suppose you wanted to work with dollars and cents in your program I.e., store and manipulate a number like: \$1.20 1.2 cannot be represented exactly in binary Floating point is not necessary For money, we will always have no more that two decimal digits.

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ECE 471 22-8 Solution Represent all money as cents instead of dollars \$1.20 == 120 cents Use integer arithmetic Results are always accurate (assuming your not using division) The two decimal digits are implied.
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