sampling theorem lab experiment

The answers to many of these questions will be discovered during the course of this experiment. It is first necessary to show that sampling and reconstruction are, indeed, possible ! The sampling theorem defines the conditions for successful sampling, of particular interest being the minimum rate at which samples must be taken.

In-Lab: 1) Build the model in Figure 1. Figure 1 CH1A: 4 V peak to peak 2kHz sinewave for message signal CH2A: Samples taken from the message signal with a sampling rate of 8.3 kHz CH2B: Recovered signal from sampled signal When you look at CH1A and CH2A, you will see the message and the sampled signal as in Figure 2. V. V. 19May2005 11:13. ms.

PRE-LAB ASSIGNMENT Given signal x(t) = sinc(t): Find out the Fourier transform of x(t), X(f), sketch them. Find out the Nyquist sampling frequency of x(t). Given sampling rate fs, write down the expression of the Fourier trans-form of xs(t), Xs(f) in terms of X(f). Let sampling frequency fs = 1Hz.

Lab activities: Build and test sampling/reconstruction circuits and study the effect of the reconstruction filter (order and cutoff frequency) on the quality of the recovered signal. Generate the spectra of the signals at different points in the sampling system.

natural sampling Natural sampling of an analog waveform (message) is examined in the experiment entitled The sampling theorem (within Volume A1 - Fundamental Analog Experiments). Natural sampling takes a slice of the waveform, and the top of the slice preserves the shape of the waveform.

The processed signals are then converted back into analog signals using a reconstruction or interpolation operation (called digital-to-analog conversion, or DAC). Sampling: To sample a continuous-time signal x (t ) is to represent x (t ) at a discrete number of points, t = nT , where T is the sampling period. The sampling theorem states that a

This module builds on the intuition developed in the sampling module to discuss the Nyquist-Shannon sampling theorem, including a full statement and a proof.

Sampling Theorem In principle you multiply the signal xc(t) with an impulse train Multiplication in time <--> convolution in frequency domain in look like in fourier domai It is still an impulse train! Why?

Study of sampling theorem, effect of undersampling. Select the Amplitide (A) of the input sine wave signal (x (t)). Select the frequency of the signal (f m) for the input signal (x (t)). Select the sampling frequency of the signal (f s ). Change the values of A, f m, and f s to observe the variation in the input and output signals.

Lecture 16: Sampling Topics covered: The sampling theorem: representation of a continuous-time signal by its samples; Aliasing: the effect of undersampling; Demonstration: sampling and reconstruction of the output of a sinusoidal oscillator; Demonstration: some practical uses of aliasing—a visit with Dr. Harold Edgerton at the MIT Strobe Laboratory.

This video demonstrate about the sampling theorem verification Lab Experiment- Analog Communication Lab

Study of sampling theorem, effect of undersampling. Select the amplitide (A) of the input sine wave signal (x (t)). Select the frequency of the signal (f m) for the input signal (x (t)). Select the sampling frequency of the signal (f s ). Change the values of A, f m, and f s to observe the variation in the input and output signals.

Sampling Theorem Sampling theorem: a signal g(t) with bandwidth < B can be reconstructed exactly from samples taken at any rate R > 2B.

Analysis of Sampling Theorem using MATLAB (01 Experiment on Digital Communication Lab) Dr. Sudip Mandal 545 subscribers Subscribed 84 8K views 3 years ago Digital Communication Lab Using MATLAB ...

Sampling Theorem: The sampling theorem specifies the minimum-sampling rate at which a continuous-time signal needs to be uniformly sampled so that the original signal can be completely recovered or reconstructed by these samples alone. This is usually referred to as Shannon's sampling theorem in the literature. Basic Simulation Lab - Sampling theorem verification

AIM OF THE EXPERIMENT: To obtain the sampled output for given modulating signal input. Verify the sampling theorem for different modulating frequencies fs< 2fm, fs= 2fm and fs >2fm. Reconstruct the original signal from the sampled signal.

Experiment 10Sampling and ReconstructionIn this experiment we shall learn how an analog signal can be sampled in the time domain and then how the same samples can b. used to reconstruct the original signal. Figure 10.1 shows the experi. ent board you will use in the laboratory. The board consists of ̄ve internally connected card edge ...

The document describes an experiment to verify the sampling theorem by sampling an analog signal and reconstructing it using a lowpass filter. Key steps include: 1. Measuring the transfer function of a 3 kHz lowpass filter by varying the input frequency and measuring voltage levels. 2. Using a pulse generator and analog switch to naturally sample a 2 kHz sine wave at 8.3 kHz, and observing the ...

The process of digitization consists of first sampling (digitization in time) and quantization (digitization in amplitude). In this experiment we will study and understand the principle of sampling, while the principle of quantization will be studied in the next experiment. The sampling process depicts an analog signal as a sequence of values.

Theory: The analog signal can be converted to a discrete time signal by a process called sampling. The sampling theorem for a band limited signal of finite energy can be stated as, scribed by specifying the values of the signal at instants of time separated by 1 It can be recovered from knowledge of samples taken at the rate of 2W per second.

This document summarizes a lab experiment on sampling theory using MATLAB. The experiment involves: 1) Generating a sinusoidal signal and sampling it at different rates, including above and below the Nyquist rate. 2) Reconstructing the signal from the sampled versions to verify if aliasing occurs below the Nyquist rate. 3) Analyzing the reconstructed signals in the time and frequency domains ...

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