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Volume 43 Issue 8
Aug.  2021
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Feng QIN, Yuan GAO, Shuang WU. Signal Compensation of Coaxial Cable Based on Modified Non-negative Tikhonov Regularization Method within Bayesian Inference[J]. Journal of Electronics & Information Technology, 2021, 43(8): 2199-2206. doi: 10.11999/JEIT210068
Citation: Feng QIN, Yuan GAO, Shuang WU. Signal Compensation of Coaxial Cable Based on Modified Non-negative Tikhonov Regularization Method within Bayesian Inference[J]. Journal of Electronics & Information Technology, 2021, 43(8): 2199-2206. doi: 10.11999/JEIT210068

Signal Compensation of Coaxial Cable Based on Modified Non-negative Tikhonov Regularization Method within Bayesian Inference

doi: 10.11999/JEIT210068
Funds:  Foundation of Key Laboratory of Science and Technology on Complex Electromagnetic Environment, China Academy of Engineering Physics (FZSYS-02)
  • Received Date: 2021-01-18
  • Rev Recd Date: 2021-03-31
  • Available Online: 2021-04-16
  • Publish Date: 2021-08-10
  • With the increase of signal frequency, bandwidth and transmission distance, the signal distortion problem brought by the coaxial cable becomes serious and can not be ignored. Specifically, if the coaxial cable is accidentally squeezed, stretched or folded during use, the signal distortion problem will become more serious. Herein, a modified signal compensation method is proposed based on the non-negative Tikhonov regularization method with Bayesian inference. This method can effectively avoid the ill-conditioned matrix problem in the inverse analysis. The input signal can be reconstructed by using impulse response function of coaxial cable and measured output signal. Three different types of pulse signals, i.e., double exponential pulse signal, modulated square wave signal, and bipolar pulse signal, transmitted in a 15 m extruded coaxial cable are compensated. The results show that this method can achieve excellent compensation effect, and the deviation between the compensated signal and the input signal is far lower than that of typical attenuation compensation method. Moreover, the modified method exhibits strong robustness. When the signal-to-noise ratio is larger than 30 dB, it can maintain good stability.
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