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Postgraduate DiplomaElectronics, Embedded Systems & Telecom Applications open

Diploma in Digital Filters, FFT and Spectral

Online postgraduate diploma of 800 hours in Digital Filters, FFT and Spectral Analysis: 8 modules covering discrete signals and systems, FIR and IIR filter design, the DFT and FFT, spectral estimation, multirate and adaptive processing, and engineering applications, with an assigned technical tutor.

Duration6–8 months
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma
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Learning outcomes

What you will be able to do

01

Analyse discrete systems using the Z-transform and frequency response.

02

Design FIR filters with window and optimal methods.

03

Design stable IIR filters in second-order structures.

04

Implement the FFT and fast convolution efficiently.

05

Estimate power spectra with non-parametric and parametric methods.

06

Apply multirate and adaptive techniques to signal processing.

07

Solve real measurement and diagnostic problems with spectral analysis.

Profile

Who it's for

  • Signal processing engineers who want a solid grounding in filter design and spectral methods.
  • Instrumentation engineers measuring and characterising signals and converters.
  • Communications systems engineers working on channelisation and sample rate conversion.
  • Predictive maintenance specialists analysing machine vibration.
  • Digital audio engineers designing filters and rate converters.
  • DSP algorithm developers implementing processing chains on DSP or FPGA.
  • Engineering or science graduates looking to enter the telecommunications sector.
Standards & tools

What you'll work with

  • IEEE 754-2019 (floating-point arithmetic)
  • IEEE 1241-2010 (terminology and test methods for analogue-to-digital converters)
  • IEEE 1057-2017 (digitising waveform recorders)
  • IEC 61000-4-7:2002 (harmonics and interharmonics measurement)
  • IEC 61260-1:2014 (octave-band and fractional-octave-band filters)
  • ISO 18431-2:2004 (signal processing for mechanical vibration and shock: windows for Fourier transform analysis)
  • IEC 61672-1:2013 (sound level meters)
  • MATLAB (Signal Processing Toolbox)
  • Python (SciPy and NumPy)
  • GNU Octave
  • pyFDA
  • LabVIEW
Syllabus

8 modules

  1. 1.1Sampling, aliasing and the Nyquist theorem
  2. 1.2Sequences and LTI systems
  3. 1.3Discrete convolution and correlation
  4. 1.4Z-transform and regions of convergence
  5. 1.5Poles, zeros and stability
  6. 1.6Frequency response and the DTFT
  7. 1.7Difference equations
  8. 1.8Quantisation and quantisation noise
  9. 1.9Fixed-point and floating-point representation
  10. 1.10Lab: analysis of LTI systems in Python
  1. 2.1Linear phase and coefficient symmetry
  2. 2.2Window method: Hamming, Kaiser and Blackman
  3. 2.3Parks-McClellan optimal design
  4. 2.4Least squares and multiband filters
  5. 2.5Differentiator and Hilbert filters
  6. 2.6Ripple and attenuation specifications
  7. 2.7Direct and transposed structures
  8. 2.8Effects of coefficient quantisation
  9. 2.9Moving-average and CIC filters
  10. 2.10Practical: band-pass filter with Parks-McClellan
  1. 3.1Butterworth, Chebyshev and elliptic prototypes
  2. 3.2Bilinear transform and prewarping
  3. 3.3Impulse invariance method
  4. 3.4Cascaded second-order sections
  5. 3.5Stability and numerical sensitivity
  6. 3.6Limit cycles and overflow
  7. 3.7Notch filters and resonators
  8. 3.8Comparison of FIR and IIR
  9. 3.9Minimum phase and group delay
  10. 3.10Lab: elliptic filter in biquad sections
  1. 4.1DFT: definition and properties
  2. 4.2Radix-2 decimation-in-time algorithm
  3. 4.3Radix-4, split-radix and arbitrary sizes
  4. 4.4Real FFT and data packing
  5. 4.5Fast convolution: overlap-add and overlap-save
  6. 4.6Computational cost and memory
  7. 4.7FFTW and CMSIS-DSP libraries
  8. 4.8Numerical precision of the FFT
  9. 4.9Goertzel algorithm for tone detection
  10. 4.10Practical: fast convolution with overlap-save
  1. 5.1Spectral leakage and windows
  2. 5.2Frequency resolution and zero-padding
  3. 5.3Periodogram and Welch's method
  4. 5.4Power spectral density
  5. 5.5Spectrogram and STFT
  6. 5.6Parametric estimation: AR and Burg
  7. 5.7Subspace methods: MUSIC and ESPRIT
  8. 5.8Measurement of SNR, SINAD and THD
  9. 5.9Amplitude calibration and scaling
  10. 5.10Lab: vibration spectrum of a machine
  1. 6.1Decimation and interpolation
  2. 6.2Polyphase filters and their efficiency
  3. 6.3Fractional sample rate conversion
  4. 6.4Filter banks and QMF
  5. 6.5Discrete wavelet transform
  6. 6.6LMS and RLS adaptive filters
  7. 6.7Envelope detection and demodulation
  8. 6.8Real-time block processing
  9. 6.9Latency and buffer size
  10. 6.10Workshop: rate conversion from 48 to 44.1 kHz
  1. 7.1Harmonic analysis according to IEC 61000-4-7
  2. 7.2Vibration-based predictive maintenance
  3. 7.3Biomedical signal processing
  4. 7.4Radar and Doppler frequency estimation
  5. 7.5Acoustics: octave and third-octave bands
  6. 7.6Characterisation of ADCs and instrumentation
  7. 7.7Digital channelisation in communications
  8. 7.8Implementation on DSP and FPGA
  9. 7.9Validation with reference signals
  10. 7.10Case study: bearing fault detection
  1. 8.1Definition of the application and requirements
  2. 8.2Signal acquisition and characterisation
  3. 8.3Filter design and comparison
  4. 8.4Spectral analysis and metrics
  5. 8.5Real-time implementation
  6. 8.6Verification and testing
  7. 8.7Documentation of results
  8. 8.8Discussion of limitations and improvements
  9. 8.9Report and presentation
  10. 8.10Final project: final review with your tutor
Methodology, software & labs

How you'll learn

The programme is delivered 100% online on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within the intake, so you can combine it with your job.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is MATLAB (Signal Processing Toolbox), Python (SciPy and NumPy), GNU Octave, pyFDA and LabVIEW, in free, academic or evaluation versions. Testing is studied through real procedures: filter design and simulation in Python, machinery vibration analysis and harmonic measurement in power networks. Assessment is continuous, module by module, plus the final project.

Standards covered: IEEE 754-2019, IEEE 1241-2010, IEEE 1057-2017, IEC 61000-4-7:2002, IEC 61260-1:2014, ISO 18431-2:2004 and IEC 61672-1:2013.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of IEEE 754, IEEE 1241 and IEEE 1057 applied to real cases, not as a theoretical annex.
Industry software:MATLAB (Signal Processing Toolbox), Python (SciPy and NumPy), GNU Octave, pyFDA and LabVIEW, in free, academic or evaluation versions.
Final project:a complete spectral processing application, from signal acquisition and filter design to real-time implementation, reviewed by your tutor.
Flexible format:100% online, no fixed timetables, compatible with full-time work.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Application and requirements
Define the target application and its measurement requirements.
Signal acquisition
Acquire and characterise the signals to be processed.
Filter design and comparison
Design and compare candidate FIR and IIR filters.
Spectral analysis and real-time implementation
Analyse the spectrum, compute metrics and implement the chain in real time.
Final project
Verify, test and document the results with their limitations, reviewed by your tutor.
Career opportunities

Where this takes you

Signal processing engineerInstrumentation engineerCommunications systems engineerPredictive maintenance specialistDigital audio engineerDSP algorithm developer
Admissions & scholarships

Requirements

  • Prior technical training or professional experience in the sector. No university degree is required.
  • An internet connection and a computer capable of running the programme software.
  • English sufficient to read technical standards.

Ready to start?

Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.

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FAQ

Frequently asked questions

The programme totals 800 hours over 6–8 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.

You work with MATLAB (Signal Processing Toolbox), Python (SciPy and NumPy), GNU Octave, pyFDA and LabVIEW, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.

A SEIUM Institute diploma, awarded on passing the continuous assessment and the final project. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.

Yes. Modules passed are recognised in a higher programme in the same area (postgraduate diploma or master's). Ask about the recognition policy when you enrol.

Prior technical training or professional experience in the sector (no university degree required), a computer able to run the programme software and English sufficient to read technical standards.

Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.

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