MentorDSP

An interactive illustration of signal processing


SIGgen | DSPpro | NUMpro | DSPbase |MATHstat | IMAGEsee | COMpro


New:

MentorDSP version 1.0

MentorDSP is an interactive educational software package focused on the illustration of digital signal processing. MentorDSP is focused on the illustration of DSP fundaments, waveform synthesis, number manipulation, Fourier transform, convolution, correlation, filter design, image processing and numerical modulations. The software includes real-time features such as sound processing, filtering and statistics. MentorDSP is simple, intuitive and straightforward to use, targeted to ease and illustrate the fundaments of digital signal processing (More...).

Available Documentation

  • Download the PPT slides and PDF of the paper presenting MentorDSP and ComPRO (Telecom09, Morocco, March 2009)
  • Download the lab practicals published by INSA on Nov. 08
  • Free for teachers in Universities: ask for a FREE copy of the manual to Etienne.Sicard <a> insa-toulouse.fr
  • A 20 pp description of MentorDSP that appeared in Magnitudesigns, 2007

Main Features

The initial screen of the tool includes seven major sections. For each section, a set of laboratory practical is proposed.

The main tools proposed in MentorDSP are:

  • SIGgen: signal generator
  • DSPpro: filtering
  • NUMpro: tutorial on formats, conversion
  • DSPbase: time, frequency domain representation of signals
  • MATHstat: tools for random signals
  • IMAGEsee : tutorial on image processing
  • COMpro: tutorial on modulations

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DSPbase

The item “Real-Time-Sound” is a good introduction to the MentorDSP philosophy. At a press of this item in the lab practical list, the screen is organized as follows. The upper screen is the time-domain representation of the sound. The sound waveform is captured in real-time from the computer microphone and appears as a series of samples (512 by default). The waveform corresponds to a human voice (male pronouncing vowels). Situated on the bottom is the real-time spectrogram of the voice. The Fourier Transform is used to compute for each set of 512 samples the frequency-domain components of the input waveform. The frequency is the Y axis while the X axis represents the time. The yellow-white spots around 200 and 4000 Hz correspond to high energy contents while the green-blue colors corresponds to very low energy.

This kind of tool has a very impressive impact on students when illustrating the concept of Fourier Transform.

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SigGen

MentorDSP can generate basic signals, modulated signals, but also user's defined equation thanks to a power set of routines. The example shown above uses time variables, pi constant and SIN function. Around 50 basic functions as well as advanced functions enable to create complex signals. Noise can also be added to the signal.

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DspPro

In the screen dedicated to Finite-Impulse-Response (FIR) filter design, the user selects the type of filter (low pass, high pass, band pass, notch), the cut-off frequency and filter order. The coefficients are then automatically computed. The result on a chirp signal may be observed (variation of the amplitude of the Y[n] signal depending on frequency). The low frequency contents are not attenuated, while the frequencies above 1000 Hz are reduced.

Similar features are offered to Infinite-Impulse-Reponse (IIR) filters. The user selects the type of filter (low pass, high pass, band pass, notch). The cut-off frequency and filter parameter numbers may be changed. The synthesis method, based on bi-quad transform inspired from analog filters, is fully detailed and illustrated.

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NumPro

In MentorDSP, a specific lab practical has been focused on the format used in digital signals. Not only floating and fixed point formats are important basic concepts of DSP, but also specific functions such as rounding or saturation. The screen enables the following features:

  • Generation of a real, binary, hexadecimal, fixed-point and floating-point number
  • Vary the desired precision 4 to 16 bits
  • Effect of saturation on fixed numbers
  • Make the conversion between the Real value Hexa, Fixed and the Binary notation

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COMPro

An important topic covered by MentorDSP concerns modulations. Most modulations are illustrated by coupling time and frequency domain representations and give access to the key parameters such as the modulation amplitude and signal frequencies. The instant spectrum shows the components of the modulated signal according to the theory. The spectrogram of the frequency modulation shows possible discontinuities due to numerical data modulation. The modulation/demodulation implemented in COMpro concern AM, FM, QPSK, GMSK, OFDM

Download a paper published at Telecom09 Agadir, Morroco, March 2009 on modulations

 

MATHstat

Correlation has been the focus of particular efforts to give the teacher ways to illustrate the core idea and step-by-step illustration of the convolution and correlation theory. MentorDSP proposes to compute the convolution between two very simple signals, i.e simple pulses X[n] and Y[n]. The idea is to display the instant value of the convolution and to observe the construction of the result. Once understood on simple cases such as constant probability density functions, convolution may be applied to complex density functions.

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IMAGEsee

In the field of Image Processing, the primary objective of the MentorDSP software is to help the student to understand the link between pixel and RGB values, discover the HSV ( Hue , Saturation, Value) coding, illustrate the correspondence in the palette. A set of basic image transforms is proposed to visualize the image inversion and Boolean operation applied to pixels. Addition of two images, substration and complex arithmetic operators iare also available.

The image compression is addressed through the Discrete Cosine Transform (DCT), and Invert DCT. The DCT is first applied to very simple images to understand the link between image pixels and frequency. The student may also visualize the impact of quantization resolution and image compression factor on the resulting image quality. Correlation, filtering, may also be applied on images.

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Contact the author at : Etienne Sicard etienne.sicard "at" insa-toulouse.fr