## Fixed-Point Signal Processing Systems

### When

Contact David
Anderson
or Wayne
Padgett to reserve your place today! On-site course
offerings can be arranged.

Click here to register
online for the Georgia Tech offering.

### Who Should Attend

The course is designed for engineers,
scientists, and
technicians who need to do signal processing on fixed-point processors. Some exposure to signal
processing is assumed
but general concepts will be briefly reviewed the first day.

### Course Objectives

Over 90% of signal processing systems
use finite-precision
(fixed-point) arithmetic. This
four-day
course presents an in-depth look into designing fixed-point signal
processing
systems. The course
includes extensive
laboratory time so that participants can explore concepts as they are
taught. The course
begins with a brief
review of pertinent DSP concepts and then continues to cover notation
and fixed-point
filtering fundamentals, noise analysis, scaling issues, multi-rate
systems, and
system performance analysis.

### Laboratories

Each day’s instruction will
include laboratory time designed
to supplement the lectures. These
laboratories are either interactive system design exercises or system
analysis projects. The
instructors will be available to work
with participants.

### Course Outline

Day 1

- DSP concepts
review – Z transforms, frequency response, convolution
- DSP concepts
review – FIR, IIR, DF1, DF2, cascade of sos filter structures
- Lab time
– MATLAB tools, zplane, freqz, butter, pmfir, tf2sos
- Random processes
– autocorrelation, power spectrum, filtering noise,
sum(h.^2)*sigma identity

Day 2

- Fixed point
– Q notation, quantization noise, multiplication, rounding
- Fixed point
– coefficient quantization, roundoff error, overflow/scaling
- Lab time
– quantizing coefficients in direct form, in cascaded sos
- Fixed point
– Analyzing roundoff error, noise power, spectrum at output

Day 3

- Lab time
– comparing roundoff noise model to simulated fixed point
filter
- Fixed point
– Analyzing overflow / scaling, computing scaling values
- Lab time
– detecting overflow, computing scale factors
- Lab time
– observing effects of scaling on noise power

Day 4

- Multirate
– polyphase FIR beats IIR
- Multirate
– staged interpolation advantages
- Lab time
– comparison of IIR to staged polyphase (order, noise power,
overflow)
- Wrap up, summary

### Course Administrators

**Dr. David V.
Anderson**

(404) 385-4979

david.anderson@ece.gatech.edu

**Dr. Wayne
Padgett**

(812)
877-8185

wayne.padgett@rose-hulman.edu