What is signal reconstruction

Signal reconstruction refers to recovering the entire signal from a known partial time domain signal or frequency domain signal; signal reconstruction technology mainly studies how to reconstruct a complete signal from partial data obtained from observation; signal reconstruction technology has It is widely used in optical communications, image processing, speech processing, geophysical signal processing, electron microscopy, astronomy, paleomagnetism, x-ray crystallography and other disciplines.

#The operating environment of this tutorial: Windows 7 system, Dell G3 computer.

What is signal reconstruction?

Signal reconstruction technology is a signal processing technique that has developed very rapidly in recent years. It mainly studies how to obtain signals from observations. Partial data reconstructs the complete signal. Signal reconstruction technology has been widely used in optical communications, image processing, speech processing, geophysical signal processing, electron microscopy, astronomy, paleomagnetism, x-ray crystallography and other disciplines, and has attracted more and more attention. .

Application

• Application in time delay estimation

In seismic exploration, ocean acoustics , radar, sonar and other fields often encounter time delay estimation problems. For example, we often encounter situations where an unknown wave propagates in multiple channels or is reflected multiple times on a single channel. Assuming that the channel has no dispersion, multiple times of this wave can be received on the receiver. The arrival signal, and the amplitude of each arriving wave is different, that is, it has a different attenuation coefficient. Since the arrival time and attenuation coefficient of a wave reflect the properties of the medium it passes through, it is required to estimate the delay and attenuation of the arriving wave from the signals received by multiple receivers.

• Application in speech processing

In speech and image processing, short-time Fourier transform is commonly used transfern (STFT for short) to represent the signal.

For example, in terms of fast transmission technology of voice signals, Portnoff has developed a transmission technology that uses STFT to transmit voice signals. For another example, for the processing of improving the speech signal-to-voice ratio, usually, the Wiener filter or spectral technique can be used to estimate the amplitude spectrum of the Fourier transform of the speech in the noise, and then combine it with the noisy phase spectrum. to get clearer speech. In this kind of processing, although the amplitude spectrum of the short-time Fourier transform is processed to improve the signal-to-noise ratio, the phase spectrum still contains serious noise, thus affecting the clarity of the recovered speech. If only Reconstructing the signal using the processed amplitude spectrum of the short-time Fourier transform will further improve the clarity of the speech, and is therefore a better way to improve the speech signal-to-noise ratio.

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