Fixed-Point Signal Processing

Front Cover
Morgan & Claypool Publishers, 2009 - Technology & Engineering - 121 pages
0 Reviews
More than 90 percent of signal-processing systems use finite-precision (fixed-point) arithmetic. This is because fixed-point hardware is lower cost and lower power, and often higher speed than floating-point hardware. The advantage of fixed-point hardware in a digital signal processing (DSP) microprocessor ( P) is largely due to the reduced data word size, since fixed-point is practical with 16 bit data, while floating-point usually requires 32 bit data. Field programmable gate arrays (FPGAs) gain similar advantages from fixed-point data word length and have the additional advantage of being customizable to virtually any desired word length. Unfortunately, most academic coursework ignores the unique challenges of fixed-point algorithm design. This text is intended to fill that gap by providing a solid introduction to fixed-point algorithm design. Readers will see both the theory and the application of the theory to useful algorithms.
 

What people are saying - Write a review

We haven't found any reviews in the usual places.

Contents

Getting Started
1
12 TOOLS
2
DSP Concepts
3
212 DIFFERENCE EQUATIONS
4
22 ZTRANSFORM DOMAIN SYSTEMS ANALYSIS
5
221 POLES AND ZEROS
7
23 BLOCK DIAGRAMS AND FILTER IMPLEMENTATION
9
231 TRANSPOSE FILTERS
10
45 FLOATINGPOINT
49
46 BLOCK FLOATINGPOINT
50
Quantization Effects Data and Coefficients
53
52 DATA QUANTIZATION
54
522 RANGES
57
523 QUANTIZATION NOISE POWER
59
524 SIGNALTONOISE RATIO
60
525 SATURATION AND OVERFLOW
62

232 CASCADED SECONDORDER SECTIONS
11
24 FREQUENCY RESPONSE
13
241 FREQUENCY RESPONSE FROM THE ZTRANSFORM
14
Random Processes and Noise
19
311 EXPECTATIONS AND MOMENTS
21
312 STATIONARY AND ERGODIC PROCESSES
23
313 DEFINITIONS AND PROPERTIES
24
32 RANDOM PROCESSES AND FOURIER ANALYSIS
25
322 POWER SPECTRAL DENSITY
26
323 FILTERING A RANDOM SEQUENCE
27
325 PERIODOGRAMS
28
Fixed Point Numbers
31
412 ADDITION
34
414 MULTIPLICATION
35
416 SIGNED BINARY REPRESENTATION
36
42 QFORMAT
41
43 FIXEDPOINT ARITHMETIC
43
431 MULTIPLICATION
44
433 ROUNDING
45
441 QUANTIZATION EXAMPLE COMPUTING Y0
46
442 QUANTIZATION EXAMPLE COMPUTING Y1
47
444 MATLAB EXAMPLE
48
53 COEFFICIENT QUANTIZATION
67
531 SIGNIFICANT FACTORS IN COEFFICIENT QUANTIZATION
68
532 2NDORDER COUPLED FORM STRUCTURE
69
533 DIRECT FORM IIR FILTERS COEFFICIENT QUANTIZATION PROBLEMS
70
534 CASCADED SECONDORDER SECTION FILTERS
73
Quantization Effects RoundOff Noise and Overflow
83
611 CALCULATION EXAMPLE
87
62 OVERFLOW AND SCALING
90
622 SCALING
91
624 L1t SCALING
92
625 Lω SCALING
94
626 L2 NORM SCALING
95
628 CASCADED SECOND ORDER SECTIONS
96
63 DESIGN EXAMPLE
101
632 OUTPUT NOISE CALCULATIONS
105
633 NOISE SPECTRUM CALCULATIONS
107
635 COMPARING DIFFERENT CHOICES
109
Limit Cycles
113
Glossary
117
Bibliography
119
Copyright

Other editions - View all

Common terms and phrases

Bibliographic information