Course Highlights:
This is a course designed to provide participants with both the fundamental and practical knowledge on Digital Signal Processing (DSP) concepts and their applications. It contains of 5 modules, which cover many basic signal processing topics like sampling and quantization, Convolution and correlation, Z-transform, Discrete Fourier transform, Fast Fourier transform, IIR and FIR filters, and application examples.
It also provides laboratory experiments to let participants have better understanding of the theories. SCILAB is used in all the experiments. This course uses a simplified, step-bystep teaching approach (module-based) that facilitates for effective DSP learning, without the usual heavy mathematical explanation.

Objective of the course:
To provide participants with both fundamental and practical knowledge in digital signal processing in a user-friendly way with lots of exercises.

Who Should Attend:
Engineer, technical support officers, and managers from the manufacturing, government and defense sectors who want to use or plan to use digital signal processing, to learn the fundamental knowledge in signal processing, to know how to use SCILAB for signal processing, or to be involved in the purchase of products that involve signal processing.

Course Outline:

Module 1: Digital Signals and Systems

• Frequency domain analysis
• Processing of analog signals using DSP techniques
• Conversion of analog signals to digital signals
• Advantages and disadvantages of digital signal processing over analog signal processing
• Signal representation in time domain
• Discrete-time systems
• Digital networks
• Linear systems
• Time-invariant systems
• Impulse response of digital systems
• Application examples
• Problems
• Laboratory exercise 1: Introduction to Scilab
• Laboratory exercise 2: Sampling theorem
• Laboratory exercise 3: Quantisation
• Laboratory exercise 4: Difference equations

Module 2: Convolution and correlation

• Discrete linear convolution
• Properties of convolution
• Deconvolution
• Cross-correlation
• Autocorrelation
• The relationship between convolution and correlation
• Application examples
• Problems
• Laboratory exercise 5: Convolution and correlation

Module 3: The Z-Transform and Frequency response

• The z-transform and inverse z-transform
• Properties of the z-transform
• System function
• Discrete-time signals and systems in the frequency domain
• Application examples
• Problems
• Laboratory exercise 6: Z-transform and system function

Module 4: The Discrete Fourier Transform

• Introduction to DFT
• Fast Fourier transform
• Convolution in frequency domain
• Correlation in frequency domain
• Application examples
• Problems
• Laboratory exercise 7: Discrete Fourier transform

Module 5: Introduction to Digital Filters, FIR digital filter design

• Introduction to digital filters
• Designing FIR digital filters using the windowing technique
-Low-pass filter
-Band-pass filter
-Band-stop filter
-High-pass filter
• Application examples
• Problems
Laboratory exercise 8: Digital filter design