DSP Projects Matlab is one of the blooming fields of research due to its widespread application. Digital signal processing based projects are implemented using Matlab due to its high mathematical functionality and toolbox support. DSP projects can be implemented using many other platforms like Matlab, Simulink and Lab view, unlike embedded systems which can be implemented only in hardware. Among these tools, Matlab is the best choice for simulation due to its wide toolbox support for DSP applications. We are working in this field for the past 10 years; we can provide best and novel ideas to implement innovative projects. Our experience and expertise makes us a knowledge hub for students who are in search of research guidance.


     DSP Projects Matlab brings out innovative ideas and concepts in DSP for the enrichment of student’s academic career. Matlab is preferred by many scholars due to its inbuilt functionalities, algorithm support, and application specific toolboxes. Major problems in DSP are frequency resolution, antialias filter, frequency resolution and quantization error. DSP is a vast and booming area for research, which is the reason for students getting attracted towards it.  We have world class developers with us, working on various concept of DSP which makes them an expert in this domain. We have discussed below the major domains of DSP, which is the base for every project implemented in DSP.

Projects in DSP can be taken based on its sub domains like:

  • Waveform generation (Discrete wavelet transform)

Major applications:

  • Communication and geophysics(1D and 2D applications)
  • Speech, audio, image and video processing
  • Biomedical Imaging and applications

Wavelet toolbox support in Matlab:

  • Used for data compression, feature extraction, image compression, time series analysis etc
  • Uses wavelet frame representation like continuous, stationary, discrete and non decimated wavelet transform.

Time and space domain:

Based on digital filters for the enhancement of the Input signal

  • Removes distortion present in the signal
  • Signal separation and restoration
  • Identifies major elements like adders, multipliers, delays and advances.
  • Maintains linear phase response and magnitude response
  • Positions ideal filter types(band pass and low pass)

Z transforms:

  • Transfer functions
  • Bilateral Z-transform
  • Unilateral Z-transform

Frequency based domain:

  • DFT(Discrete Fourier transform) and DTFT
  • Discrete Fourier series
  • Fast Fourier transform
  • Zero padding(DFT)
  • Fast Fourier transform

Major applications of DSP:

  • Audio and speech processing (Equalization, speech recognition and synthesis, compression and encryption)
  • Image and video processing(coding for storage and transmission, robotic vision, animation and enhancement)
  • Military applications(missile guidance, secure communication etc)
  • Seismological applications
  • Sensor data processing
  • Space applications(radar and sonar processing)
  • Biomedical and healthcare applications(X-ray analysis, ECG analysis, EEG brain mappers)
  • Sensor data processing
  • Sound reinforcement applications
  • Economic and weather forecasting
  • Consumer electronics – Interactive entertainment, Internet voice and video, digital camera etc.


       We have provided a brief insight about the domains and applications of DSP, which the students must understand before taking a project in DSP. Students can approach us any time with their queries; we are there to support you.