The Nyquist theorem is a property of mathematics and has nothing to do with
technology. It says that if you have a function whose Fourier spectrum does
not contain any sines or cosines above f, then by sampling the function at a frequency of 2f you capture all the information there is. Thus, the Nyquist
theorem is true for all media.
The Nyquist theorem is a property of mathematics and has nothing to do with technology. It says that if you have a function whose Fourier spectrum does not contain any sines or cosines above f, then by sampling the function at a frequency of 2fyou capture all the information there is. Thus, the Nyquist theorem is true for all media.
The Nyquist theorem defines the maximum bit rate of a noiseless channel.
Hi Please send a list of Mphil thesis Topics and full thesis report for clouding computing as well as data mining
Nyquist has shown that C=2 B log2 (M) [bps] C: Capacity B: Bandwidth M: Signaling Levels log2 (x)= [ log10 (x) / log10 (2) ] So We assume F1=0Hz F2=20kHz so B= F2-F1=20000 Hz C = 2*20000* log2 (16) = 2*20000* log10 (16) / log10 (2) = 160 000 bps
Bell curves are used because they represent an exactly normal distribution. A normal distribution means that all of the values are centered around a single mean value, with the probability density decreasing equally on either side of the mean. This is the distribution that is most widely used in statistics because it is often found naturally (truly random data follows a normal distribution), and also because it follows from the central limit theorem.
I cannot see where the Nyquist theorem relates to cables, fiber or not.The theorem I know, the Nyquist-Shannon sampling theorem, talks about the limitations in sampling a continuous (analog) signal at discrete intervals to turn it into digital form.An optical fiber or other cable merely transport bits, there is no analog/digital conversion and no sampling taking place.
The Nyquist theorem is a property of mathematics and has nothing to do with technology. It says that if you have a function whose Fourier spectrum does not contain any sines or cosines above f, then by sampling the function at a frequency of 2fyou capture all the information there is. Thus, the Nyquist theorem is true for all media.
The Nyquist theorem is a property of mathematics and has nothing to do with technology. It says that if you have a function whose Fourier spectrum does not contain any sines or cosines above f, then by sampling the function at a frequency of 2f you capture all the information there is. Thus, the Nyquist theorem is true for all media.
The Nyquist theorem defines the maximum bit rate of a noiseless channel.
in automatic control the nyquist theorem is used to determine if a system is stable or not. there is also something called the simplified nyguist theorem that says if the curve cuts the "x-axies" to the right of point (-1,0) then the system is stable, otherwise its not.
The Nyquist Theorem states that an audio sample should be taken with sufficient deviation compensated for. For instance if a volume comes in at 30 DB then the sample should range all the way up to 60 DB.
Answer The most common sampling theorem is known from Harry Nyquist, 1889 -1976. It is the foundation of digital audio. In 1928, Nyquist wrote a paper called "Certain Factors in Telegraph Transmission Theory" where he proved that for complete signal reconstruction, the required frequency bandwidth is proportional to the signaling speed, and that the minimum bandwidth is equal to half the number of code elements per second.
Hi Please send a list of Mphil thesis Topics and full thesis report for clouding computing as well as data mining
Hi Please send a list of Mphil thesis Topics and full thesis report for clouding computing as well as data mining
According to the Nyquist theorem, a sample rate of double the frequency is required to record it, so 40 kHz .
Use Nyquist and Shannon Heartly theorem to solve this Nyquist theorem says that Channel Capacity C = 2 * Bandwidth * log2 (Number of Signal levels) Shannon Heartly theorem says that Channel Capacity C = Bandwidth * log2( 1 + SNR) Important points to consider while solving Bandwidth is expressed in Hz SNR is expressed in dB it must be converted using dB value = 10 log10(SNR) (10 dB = 10, 20 dB = 100, 30 dB = 1000 etc..)
The Nyquist Theorem says that the sampling frequency should be twice the bandwidth to avoid aliasing. Thus if the bandwidth of the system is bw then the sampling frequency f=2*bw.