Assessment of Signal Distortion Removal in the Noisy Environments
Abstract
The study of digital signal processing (DSP) has become increasingly significant over the past few decades, both academically and operationally. The creation and application of affordable software and hardware is a key factor in its commercial success. DSP algorithms are now being used in new technologies and applications across many industries. Electronics and communication engineers with experience in DSP will be in more demand as a result of this. In this article, we have sampled various analog signals with different frequencies. We have study Uniform Quantization, A-Law and Mu-Law Transformation based quantization as well as Quantization after adding noise. We have applied different filtering techniques to remove noise. We have used Wiener filter for noise cancellation. A bandpass signal with a bandwidth of 25 KHz is input. It is enough to sample bandpass signals at a rate twice the bandwidth of the signal in order to enable accurate reconstruction. We discovered that depending on the sampling rate, we either get a positive or a negative (flipped) representation of the original spectrum.
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