signal to noise ratio (SNR)

How does matlab measure snr of an audio signal?

Why i got negative value of SNR in matlab, Because if i measure using sound level meter in real life the snr of an audio should be high?

Answer 1

[Daniel Pollard]

According to the documentation,

"r = snr(x,y) returns the signal-to-noise ratio (SNR) in decibels of a signal, x, by computing the ratio of its summed squared magnitude to that of the noise, y. y must have the same dimensions as x. Use this form when the input signal is not necessarily sinusoidal and you have an estimate of the noise."

In other words,

r can be negative because it's measured in dB, so if the sum of the squares of the noise y exceeds the sum of the squares of the signal x, the argument of the logarithm is between 0 and 1, so the logarithm is negative.

[muhammad nur adri nawi]

thank you

[muhammad nur adri nawi]

Thank you for answering my question, i have one more question sir.

If i got negative value of SNR does it mean the signal quality is low ? And how to measure noise level of a noise audio signal ? Did using fvtool function will help ?

Answer 2

[sofia]

The purpose of the work is the theoretical and experimental study, with the use of simulation in Matlab, the performance of a digital telecommunication system. We consider it below Digital Telecommunication System model A sequence of bits appears at the input of the system. To improve its performance system, based on the average bit error probability criterion, you will implement a simple channel coding which is repetition coding. According to her repeating the same bit of information multiple times. Specifically, every bit that reaches the encoder input is repeated N times (where N ϵ {1,3,…,}). The output of the encoder goes as an input to the digital modulator where the matching is done of the input bits to the input symbols, in the following way Bit Symbol

0 +𝐴

1 -A 𝑃𝑒 = 𝑄 (√ 𝐸𝑠/ 𝜎𝑤 ^2 ), 𝐸𝑠 = 𝐴 2 , PΒ = Pe Next, demodulation takes place where the received symbols are mapped to bit using the previous table. In the end, her procedure is carried out decoding according to which in each N symbols used during coding, the number of aces and zeroes is counted and a decision is made in favor of the digit that appears most times. To calculate the mean (experimental) bit error probability (BEP) relation can be used PB = Fe/ 2 Note that Es=2Eb, where Eb is the average bit energy. For the corresponding mean calculation of bit error probability using coding you will use the previous relation to combined with the fact that a Binomial random variable is created. Specifically, we have one sequence of N independent Bernoulli trials with an equal probability of "success" in each of them with PB. Need to calculate the cumulative probability of ⌈ occurring 𝛮 /2 ⌉,⌈ 𝛮 /2 ⌉ + 1, … , 𝛮 bit errors. Finally note that (𝑆𝑁𝑅)𝑑𝐵 = 10𝑙𝑜𝑔10 ( 𝐸𝑠/ 𝜎𝑤 ^2)