/Signal-Equalizer

This application allows users to open signals and manipulate the magnitude of specific frequency components through an intuitive graphical user interface. It serves various modes catering to different scenarios, providing a comprehensive toolset for signal equalization.

Primary LanguagePython

SignalEqualizer Pro

SignalEqualizer Pro is a professional desktop application designed for signal manipulation in the fields of music, speech, and biomedical applications. This versatile tool provides an intuitive interface for users to open signals, adjust frequency components, and reconstruct the output signal. With various modes, customizable windows, and synchronized viewers, SignalEqualizer Pro offers a comprehensive set of features for signal equalization.

Key Features

  • Uniform Range Mode:

    • Divide the total frequency range into 10 equal parts, each controlled by a dedicated slider.
  • Musical Instruments Mode:

    • Sliders control the magnitude of specific musical instruments in a mixed music signal (at least four instruments).
  • Animal Sounds Mode:

    • Sliders control the magnitude of specific animal sounds in a mixture of at least four animal sounds.
  • ECG Abnormalities Mode:

    • Four ECG signals, including normal and three with specific arrhythmias.
    • Sliders control the magnitude of arrhythmia components in the input signal.
  • Multiplication/Smoothing Windows:

    • Four available windows (Rectangle, Hamming, Hanning, Gaussian) for frequency range multiplication.
    • User customization of window with visual feedback.
  • Mode Switching:

    • Seamless switching between modes through a combobox.
  • Cine Signal Viewers:

    • Two linked cine signal viewers for input and output signals.
  • Spectrograms:

    • Two spectrograms for input and output signals.
    • Real-time update reflecting changes made through equalizer sliders.
    • Option to toggle show/hide spectrograms for a clutter-free interface.

Preview

watch demo

Acknowledgments

This project was supervised by Dr. Tamer Basha & Eng. Abdallah Darwish, who provided invaluable guidance and expertise throughout its development as a part of the Digital Signal Processing course at Cairo University Faculty of Engineering.

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