NU-LAGUNA
COLLEGE OF ENGINEERING and ARCHITECTURE
Name/Section
Avenido, Keirk Ian V.
CpE221A
Date performed
05/ 05/ 25
Rating
Date submitted
EXPERIMENT NO.5
DSP REAL TIME PROCESSING
OBJECTIVE/S:
This activity aims to:
When you have completed this unit, you will be familiar with two aspects of DSP technology that
are essential for real time processing.
LEARNING OUTCOMES (LOs)
At the end of the activity, the students
should be able to:
COURSE LEARNING OUTCOMES (CLOs)
1
will understand the sampling and
conversion of signals between analog
and digital forms.
•
Using and optimizing one of the most
poweful tools available to the DSP
developer
•
2
3
4
•
The Fourier Transform
COURSE LEARNING OUTCOMES (CLOs)
When you have completed this unit, you will be familiar with two aspects of DSP technology that
are essential for real time processing.
BACKGROUND INFORMATION:
APPARATUS:
1. FACET® base unit
2. DSP circuit board
3. DC MULTIMETER
4. Two-post connectors
5. Terminal posts
6. Oscilloscope
PROCEDURE:
When the output signal is square wave, the input signal is sine wave.
Wave frequency rises according to the oscilloscope.
For the chosen sample rate, the Nyquist rate is 8000 Hz.
to guarantee the input signal's quality during
conversion.
The output waveform has a frequency of 3000 Hz. Aliasing happens when the frequency of the
input signal is higher than half of the sampling rate (Nyquist frequency). Distortion results from
the output frequency acting as a "mirror" of the input frequency around the Nyquist frequency.
Since the input signal frequency (1000 Hz) is near the Nyquist frequency (1000 Hz), the
output waveform is significantly distorted with a sampling rate of 2000 Hz.
DIP SW
0000 0001
0000 0010
0000 0011
0000 0100
0000 0101
0000 0110
SAMPLING RATE
WAVEFORMS
The waveforms are nearly the same.
The frequency of the output waveform is between 500 and 800 Hz, however as the
sampling rate drops, the signal quality deteriorates. Because there aren't enough
samples per cycle at very low sampling rates, the output may exhibit aliasing or
seem like a lower-frequency copy of the original signal.
0.67
3000
1.33
6000
9000
2.00
9000
15000
2.67
12000
21000
The Nyquist rate is 3000 Hz at a sample rate of 6000 Hz. Above this
frequency, alias will occur.
There is no more signal at 5000Hz.
The post-filter eliminates aliased replicas while the filters are turned on, leaving only
the original 2250 Hz signal.
QUESTIONS:
1. Why is it necessary to sample an analog signal before processing it with a DSP?
A digital device that can only handle discrete binary information is called a DSP (Digital
Signal Processor). A continuous analog signal is transformed into discrete-time values
through sampling, which can subsequently be quantified and digitally represented. This
enables the DSP to mathematically modify the signal for applications such as frequency
analysis, noise reduction, and filtering.
2. When sampling an analog signal, what condition is necessary to ensure that the
samples adequately represent the analog signal?
The Nyquist Sampling Theorem, which states that the sampling frequency must be at
least twice as high as the highest frequency component in the analog signal in order to
prevent aliasing and enable perfect signal reconstruction, must be satisfied by the
sampling rate to guarantee that samples accurately represent an analog signal.
3. Referring to Question 2, what measures could be taken if this condition is not
respected?
Using an anti-aliasing low-pass filter prior to sampling to eliminate frequencies
above half the sampling rate, raising the sampling rate to meet the Nyquist
criterion, or using oversampling techniques—in which the signal is first
sampled at a much higher rate before being digitally filtered and down
sampled—are some corrective measures that can be used if the Nyquist
condition is not met.
4. What is the purpose of post filter at the output of a D/A converter?
A D/A converter's post-filter at the output performs the vital task of eliminating highfrequency harmonics and artifacts brought about by the digital-to-analog conversion
process, especially the box-like waveform produced by the sample-and-hold
operation. It also smoothes the signal to precisely recreate the original analog
waveform and get rid of any aliasing elements that may still be present.
5. What happens between samples at the output of a D/A converter and how does
this effect the D/A converted signal.
The D/A converter's sample-and-hold circuitry keeps the output voltage
constant between samples, resulting in a stepped staircase waveform that
introduces high-frequency distortion components at multiples of the sampling
rate and causes aperture distortion by attenuating higher frequencies. The postfilter then corrects these effects to restore the fidelity of the signal.
INTERPRETATION/ANALYSIS OF DATA
-
Real-time digital signal processing (DSP) is the process of instantaneous analysis
and interpretation of received data upon receipt, devoid of delays that may
compromise the performance of systems. This concept is important where timing is
pertinent, like audio and speech, biomedical signal tracking, radar equipment, and
communication. Algorithms are required to be extremely optimized when it comes
to real-time DSP to process the signals within rigorous time limits with the aim of
providing correct responses in good times. The essence of real-time processing is its
capacity to process continuous streams of data and dynamically change based on the
characteristics of the incoming signal. This enables systems to respond immediately
to an environment's changes, for which it is quite appropriate for control systems,
adaptive filtering, and real-time diagnostics. With real-time DSP efficiently
analyzing signals in real-time, overall modern embedded and interactive system
functionality and reliability are increased.
CONCLUSIONS AND RECOMMENDATIONS
-
In summary, real-time digital signal processing is a crucial function in making systems
react in real-time to dynamic inputs, providing precision and efficiency in different
applications. Its capacity for on-the-fly analysis and interpretation of data provides ease
of integration in communications, healthcare, and control systems. With continuing
advances in technology, the need for faster, more dependable real-time DSP solutions
increases, setting limits on what embedded systems and smart devices can do. In the
end, real-time DSP not only improves system performance but also expands the
potential for innovation in actual, time-constrained environments.