value. (2) If j
^
Skj below the maximum but has a nearly constant value, there is
a high probability that the spectrum at that frequency is due to low-energy speech.
Therefore taking the minimum will retain the information. (3) If j
^
Skj is greater than the
maximum, the bias is sufficient. Thus the estimated spectrum j
^
Skj is used to
reconstruct the output speech. However, with this approach high-energy frequency
bins are not averaged together. The disadvantages to the scheme are that more storage
is required to save the maximum noise residuals and the magnitude values for three
adjacent frames, and more computations are required to find the maximum value and
minimum value of spectra for the three adjacent frames.
9.7 Projects Using the TMS320C55x
This section provides a list of experimental projects and applications that are related to
communications at different levels. A large project can be partitioned into smaller
modules and each portion may be simple in terms of algorithm development, simula-
tion, and DSP implementation. The algorithms range from signal generation, error
correction coding, filtering, to channel simulation.
9.7.1 Project Suggestions
Some DSP applications that can be used as the course projects for this book are listed in
this section. Brief descriptions are provided, so that we can evaluate and define the
scope of each project. The numbers in the parentheses indicate the level of difficulty of
the projects, where the larger the number, the greater the difficulty.
Signal Generation and Simulation
1. White Gaussian noise generator (1)
2. Sinusoidal signal generator (1)
3. Telephone channel simulator (2)
4. Wireless fading channel simulator (2)
Adaptive Echo Canceler and Equalizer
5. Adaptive data echo canceler for dial-up modem applications (3)
6. Adaptive acoustic echo canceler for speakerphone applications (3)
7. Adaptive channel equalizer (2)
8. Adaptive equalizer for wireless communications (3)
PROJECTS USING THE TMS320C55X
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