Howtosignalprocessing
- What is signal sampling theorem?
- What is the DT signal obtained after sampling?
- How do you determine the sampling theorem?
- What is FS and FM in sampling theorem?
What is signal sampling theorem?
The sampling theorem essentially says that a signal has to be sampled at least with twice the frequency of the original signal. Since signals and their respective speed can be easier expressed by frequencies, most explanations of artifacts are based on their representation in the frequency domain.
What is the DT signal obtained after sampling?
What is the discrete-time signal obtained after sampling the analog signal x(t)=cos(2000*pi*t)+sin(5000*pi*t) at a sampling rate of 5000 samples/sec? =>x(n)=cos(0.4*pi*n)+sin(pi*n).
How do you determine the sampling theorem?
Sampling Theorem Formula
Then x(t) can be recovered in its original form if the sampling frequency is greater than or equal to twice the maximum frequency of the message signal x(t). If ωs≥2ω𝑚𝑎𝑥 (Nyquist sampling rate condition); x(nTs) = x(t), n=0, ±1, ±2, ±3, …… Here Ts is the sampling period (sec/sample).
What is FS and FM in sampling theorem?
The sampling theorem can be defined as the conversion of an analog signal into a discrete form by taking the sampling frequency as twice the input analog signal frequency. Input signal frequency denoted by Fm and sampling signal frequency denoted by Fs. The output sample signal is represented by the samples.
