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Self-paced Advanced

Real-Time Digital Signal Processing

3(118)

1 enrolled

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Trainers Rating: 3(118)
Course type: Watch to learn anytime
Duration: 1019 min
Start: Anytime
Language: English
Views: 370

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Why enroll

This course helps learners build a clear and practical understanding of digital signal processing, not just theory. It teaches how DSP concepts are applied in real time using actual hardware and software tools, making learning more hands-on and meaningful. The course also strengthens core engineering fundamentals for students from Electrical, Electronics, and Embedded Systems backgrounds. By the end, learners are better prepared for advanced studies, projects, and jobs in electronics, communication, and real-time systems, while gaining useful skills for real-world applications such as audio and video processing, control systems, radar, and communication technologies.

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Engineering Academy

Project Engineer

Learn Without Limits: Free Engineering Courses

Total experience: 5+ years
Location: India

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Course details

This Real-Time Digital Signal Processing (DSP) course helps learners understand how signal processing works in real engineering systems, not just in textbooks. It combines basic DSP concepts with practical, real-time implementation, making it useful for students and professionals.The course starts with simple signal fundamentals, explaining how analog signals are converted into digital form. It then introduces key DSP tools like discrete-time signals, FFT, and Z-transform, with focus on how they are used in real-time applications.Learners also gain hands-on experience with DSP software and hardware using tools like Code Composer Studio (CCS). Topics such as digital filters (FIR/IIR), real-time constraints, ADC/DAC interfacing, and optimization are explained clearly.By the end of the course, learners are confident in analyzing and implementing real-time DSP systems used in audio, communication, control, and embedded applications.

Source: NPTEL – Indian Institute of Science (IISc), Bengaluru [Youtube Channel]

Course suitable for

Is this course for you?

Perfect for

You work in Automotive
You're a Electrical Engineering professional
You have 3+ years of hands-on experience in this field
You want to build skills in Engineering & Design, Project Management

Before you enrol

Advanced level — assumes working knowledge of Electrical Engineering
Self-paced video, 1019 min — watch anytime

New to Electrical Engineering? Browse beginner courses →

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Course curriculum

The course is readily available, allowing learners to start and complete it at their own pace.

30 lectures16 hr 59 min

Introduction
19 min
Basics of Signal Processing
45 min
Lab - CCS
46 min
Number System
47 min
Architecture 1
46 min
Architecture 2
35 min
Real-time Constraints
45 min
FIR - Filters
43 min
Pipelining and Parallel Processing for Low Power Applications
30 min
Pipelining and Parallel Processing for Low Power Applications II
27 min
IIR Filters - 1
31 min
Lab: Sine Generation
21 min
IIR Filters - 2
38 min
IIR Filters - 3
29 min
FIR and IIR Filter in MATLAB using GUI
30 min
IIR Filter as Resonator
29 min
Lab: Real-Time Audio Output through Sine Generation
27 min
IIR Filters 4
38 min
Lab: FIR Filter in generation of music
31 min
Lab: Real-Time Audio Output through FIR Filter
30 min
DFT, DTFT, twiddle factors, properties, circular convolution and examples
35 min
Different ways of implementing FFT in CCS
33 min
Complexity of Filtering and the FFT
35 min
Lab: Filtering Using FFT
32 min
Lab: FFT in CCS
35 min
FFT - 1
36 min
FFT - 2
32 min
Overlap Add and Save Method using MATLAB
23 min
FFT - 3
34 min
Overlap Save Method
37 min

Key topics covered

Introduction to real-time DSP and its real-life uses.
Basic signal concepts, sampling, and quantization.
Number systems and discrete-time signals for DSP.
Z-transform and FFT basics for signal analysis.
FIR and IIR filters and how they work in practice.
Time and frequency domain analysis of signals.
Real-time data capture and processing methods.
Hands-on DSP coding using CCS tools.
Fixed-point and floating-point basics explained simply.
Memory and timing issues in DSP systems.
ADC and DAC interfacing for real-time signals.
Interrupts and DMA for faster processing.
DSP code optimization for better performance.
Audio signal processing using DSP.
Mini projects and system integration in DSP.

Opportunities that await you!

Skills & tools you'll gain

Engineering & Design

Project Management

Research & Developmnet

Career opportunities

Frequently asked questions

Q: You're on-site for ECU bring-up and searching "DSP ADC anti-alias filter field acceptance test procedure". The supplier DSP board passed FAT, but you're doing pre-commissioning. What sequence gives confidence that real-time sampling meets the Nyquist intent before you sign the ITP?

A: This achieves proof that the entire signal chain behaves correctly under real sampling conditions, not just on paper. B fails because clock health alone says nothing about aliasing at the ADC input. C assumes ideal components and ignores tolerance stack and layout parasitics. D waits for a system-level symptom that may never appear during a short run yet still violate sampling theory.

Q: While checking the GA and schematics and googling "DSP clock domain mismatch schematic vs datasheet", you notice the DSP datasheet lists a 200 MHz core clock, but the timing diagram on the drawing shows processing blocks budgeted at 160 MHz. What action aligns with ISO 26262 expectations?

A: This forces the safety case to close against the limiting condition instead of optimistic marketing numbers. B drops the possibility that the board-level implementation constrains the clock. C invents a value with no traceability to any controlled document. D confuses absence of observed failure with proven timing margin.

Q: During tuning you're searching "real-time DSP control loop phase lag sudden increase". The sampling period is doubled to reduce CPU load. What downstream effect should you expect first, and what's the right response?

A: This recognizes that discrete-time delay directly eats phase margin and must be addressed at the controller level. B misattributes a timing effect to noise shaping. C mixes up sampling rate with resolution. D ignores the math of zero-order hold and computational delay.

Q: You're stuck and type "estimate DSP FIR filter CPU load real-time". A 128-tap FIR runs at 20 kHz on a single-core DSP. Roughly how much of a 200 MHz core does the filter consume assuming one MAC per cycle?

A: This back-calculates the operation count and compares it to available cycles with a clear margin. B misunderstands that every sample needs the full tap set. C relies on folklore rather than arithmetic. D jumps to worst-case effects without showing they close the gap.

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