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Why you are using sampling theorem in communication systems?
sampling is a one type of process use for converting into analog signal to digital signal.
What is up sampling and down sampling?
Upsampling is the process of increasing the sampling rate of a signal. For instance, upsampling raster images such as photographs means increasing the resolution of the image.In signal processing, downsampling (or "subsampling") is the process of reducing the sampling rate of a signal. This is usually done to reduce the data rate or the size of the data.
What does Sampling Theorem refer to?
Sampling Theorum is related to signal processing and telecommunications. Sampling is the process of converting a signal into a numeric sequence. The sampling theorum gives you a rule using DT signals to transmit or receive information accurately.
What is the sampling rate in Hz?
Sampling rate is a defining characterstic of any digital signal. In other words, it refers to how frequently the analog signal is measured during the sampling process. Compact disks are recorded at a sampling rate of 44.1 kHz.
What is meant by sampling in analog to digital conversion?
while conversion of analog signal to digital signal, we need to convert continuous analog signal to discrete signal. this can be done by dividing the analog signal into specific time slots. this process is known as sampling. there is a condition for sampling that can be given as follows. fs<=2fm
Comment the effect of oversampling on a signal?
Oversampling is part of signal processing. It is the process of using a sampling frequency that is higher than the Nyquist rate to sample a signal.
What is the instantaneous sampling?
Instantaneous sampling is one method used for sampling a continuous time signal into discrete time signal. This method is called as ideal or impulse sampling. In this method, we multiply a impulse function with the continuous time signal to be sampled. The output is instantaneously sampled signal.
Statement of sampling theorem?
sampling theorem is used to know about sample signal.
How does the Sampling rate affect frequency?
In signal processing, sampling is the reduction of a continuous signal to a discrete signal. A common example is the conversion of a sound wave (a continuous signal) to a sequence of samples (a discrete-time signal).
What happens if sampling theory apply to low pass signal?
state and prove sampling theory as applied to low pass signal
What is targeted sampling in research studies?
I would like to sample the signal Xa(t) =1+cos(10 *pi*t) using sampling frequency fs=8 Hz. How can I calculate this? ANSWER: Your signal has a frequency component of 5hz (from the equation: 2*pi*f*t = 10*pi*t, therefore f=5). The Nyquist rate for this signal (the minimum sampling rate required to reconstruct the signal) is then 10Hz, and even at that rate the amplitude of the sampled signal will be reduced unless you can somehow synchronize the sampling with the peaks/troughs of the cosine signal. If you sample at 8Hz you will not be able to reconstruct the signal at all.
What are the differences between sample and interpolation methods in signal processing?
In signal processing, sampling involves taking discrete points from a continuous signal, while interpolation is the process of estimating values between those sampled points to reconstruct the original signal. Sampling reduces the amount of data, while interpolation helps fill in the gaps between sampled points to recreate a continuous signal.
