By Saeed V. Vaseghi
Complex electronic sign Processing and Noise aid, 3rd variation, offers a completely up to date and established presentation of the speculation and functions of statistical sign processing and noise aid tools. Noise is the everlasting bane of communications engineers, who're constantly striving to discover new how one can enhance the signal-to-noise ratio in communications structures and this source can help them with this job. this can be a useful textual content for senior undergraduates, postgraduates and researchers within the fields of electronic sign processing, telecommunications and statistical facts research. it is going to additionally attract engineers in telecommunications and audio and sign processing industries.
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Additional resources for Advanced digital signal processing and noise reduction
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Noise and Distortion 40 multi-path effect, in which the transmitted signal may take several different routes to the receiver, with the effect that multiple versions of the signal with different delay and attenuation arrive at the receiver. Channel distortions can degrade or even severely disrupt a communication process, and hence channel modelling and equalization are essential components of modern digital communication systems. Channel equalization is particularly important in modern cellular communication systems, since the variations of channel characteristics and propagation attenuation in cellular radio systems are far greater than those of the landline systems.
If the sampling frequency is less than 2Fs, then the adjacent repetitions of the spectrum overlap and the original spectrum cannot be recovered. The distortion, due to an insufficiently high sampling rate, is irrevocable and is known as aliasing. This observation is the basis of the Nyquist sampling theorem which states: a band-limited continuous-time signal, with a highest 24 Introduction Time domain Frequency domain x(t) X(f) 0 B –B t f 2B × * Impulse-train-sampling function ... Ts = xp(t) P( f ) = ∞ ∑ δ ( f − kF ) s k = −∞ ...
Advanced digital signal processing and noise reduction by Saeed V. Vaseghi