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When analog voice signal converts into digital signal the bandwidth needs 64kbps. Why?
PCM technique is used to convert analog voice signals into digital. In PCM the analog frequency is first sampled and then converted into binary bits. Each samples are taken as 8bits long. Basic communication theory requires that a minimum sampling rate of twice the frequency of the signal to be sampled will result in an accurate representation of the original signal.Human voice can have max 4000hz frequency, therefore sampling rate should be 8000 samples/sec.Which implies required bit rate for transmitting voice is 8000*8 = 64000 bits/sec = 64kbps.
Why the linear combination of a low frequency intelligence signal and a high frequency carrier signal is not effective as a radio transmission?
to shift the frequency of information signal ,at the frequency domain to a higher frequency ...so the information can be transmitted to the receiver.
What does frequency of a signal measure?
repetition rate of signal
Is the frequency domain plot of a voice signal discrete or continuous?
The frequency domain of a voice signal is normally continuous because voice is a nonperiodic signal.
What is meant by a low pass signal?
A low pass signal whose bandwidth is much smaller than its center frequency, such as an AM signal. It is a a signal with its spectrum concentrated around zero frequency.
What is Nyquist frequency?
The Nyquist frequency is defined as half of the sampling rate of a discrete signal processing system. It represents the highest frequency that can be accurately represented when sampling a continuous signal without introducing aliasing. According to the Nyquist-Shannon sampling theorem, to avoid distortion, a signal must be sampled at least twice the highest frequency present in the signal. For example, if a signal is sampled at 1000 Hz, the Nyquist frequency would be 500 Hz.
How would you define nyquist rate?
The Nyquist frequency should not be confused with the Nyquist rate, which is the minimum sampling rate that satisfies the Nyquist sampling criterionfor a given signal or family of signals. The Nyquist rate is twice the maximum component frequency of the function being sampled. For example, the Nyquist rate for the sinusoid at 0.6 fs is 1.2 fs, which means that at the fs rate, it is being undersampled. Thus, Nyquist rate is a property of a continuous-time signal, whereas Nyquist frequency is a property of a discrete-time system.When the function domain is time, sample rates are usually expressed in samples/second, and the unit of Nyquist frequency is cycles/second (hertz). When the function domain is distance, as in an image sampling system, the sample rate might be dots per inch and the corresponding Nyquist frequency would be in cycles/inch.
What is nyquist sampling?
Nyquist sampling refers to the principle that to accurately capture a continuous signal, it must be sampled at least twice the highest frequency present in that signal. This minimum sampling rate is known as the Nyquist rate. If the sampling rate is lower than this threshold, it can lead to aliasing, where higher frequency components are misrepresented as lower frequencies, distorting the signal. This concept is crucial in fields like digital signal processing and telecommunications.
How is it possible to represent a complex exponential signal with a frequency of 20Hz using a sampling frequency of 30Hz?
A 20Hz signal must be sampled at a minimum of 40Hz to have a chance of sampling both peaks and to get a reasonable representation it must be sampled at a minimum of 100Hz.For a sampling rate of 30Hz the Nyquist frequency is 15Hz and since 20Hz is above that it will generate the alias signal of 10Hz in the sampled data instead of the original signal of 20Hz. Therefore it is not possible to do what you ask.
What happens if we sample the signal at sampling frequency nearer to signal frequency?
If you sample at more than the Nyquist frequency (one half the signal frequency) you introduce an aliasing distortion, seen as sub harmonics.
Why are analog waveforms sampled 8000 times every second?
The frequency range for a voice signal is 300 to 4000 HZ. The Nyquist theorem states a waveform should be sampled at 2 times its highest frequency. So 2 x 4000 is 8000 samples every second. This ensures an adequate representation of the signal.
What is the nyquist sampling rate and nyquist frequency for frequency f equals 0?
The Nyquist sampling rate is defined as twice the highest frequency present in a signal to avoid aliasing during sampling. For a frequency ( f = 0 ), the Nyquist sampling rate would also be ( 0 ) since there are no oscillations to capture. Consequently, the Nyquist frequency, which is half of the sampling rate, is also ( 0 ). This means that no information can be effectively captured or reconstructed from a signal that is constant (i.e., with a frequency of zero).
What is difference between aliasing and folding in digital signal processing?
Aliasing and folding are both phenomena that occur in digital signal processing when sampling signals. Aliasing refers to the misrepresentation of a signal that occurs when it is sampled below its Nyquist rate, causing higher frequency components to appear as lower frequencies in the sampled signal. Folding, on the other hand, specifically describes the folding of frequency components back into the Nyquist interval when sampling, making it a visual representation of aliasing in the frequency domain. In essence, aliasing is the general term for the distortion caused by insufficient sampling, while folding describes the specific way that frequencies are reflected into the observable spectrum.
Procedure of Eliminating aliasing effect?
To eliminate aliasing effects in a signal processing context, one can use a low-pass filter (anti-aliasing filter) before sampling the signal. This filter removes high-frequency components that could distort the representation of the signal when sampled at a rate lower than the Nyquist frequency. Additionally, ensuring that the sampling frequency is at least twice the highest frequency present in the signal (according to the Nyquist theorem) can help prevent aliasing. Finally, applying techniques like oversampling or using digital signal processing methods can further mitigate aliasing effects.
Why is it important to band limit a signal before sampling it?
Band limiting a signal before sampling is crucial to prevent aliasing, which occurs when higher frequency components of the signal are misrepresented as lower frequencies due to insufficient sampling rates. According to the Nyquist-Shannon sampling theorem, a signal must be sampled at least twice its highest frequency to accurately capture its information. By band limiting, we ensure that only the relevant frequency components are present, allowing for accurate reconstruction of the original signal after sampling. This helps maintain the integrity and quality of the sampled data.
Definetion of nyquist rate in digital communication?
if the sampling rate is twice that of maximum frequency component in the message signal it is known as nyquist rate
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.
