The use of WGN and AWGN functions of white noise in matlab

The use of the WGN and AWGN functions of white noise in MATLAB is as follows:

MATLAB produces Gaussian white noise is very convenient, can directly apply two functions, one is WGN, the other is AWGN. The WGN is used to generate Gaussian white noise, and AWGN is used to add Gaussian white noise to a signal.

1. WGN: Generate Gaussian white noise
y = WGN (m,n,p) produces a Gaussian white noise matrix of M row n columns, and p specifies the intensity of the output noise in DBW units.
y = WGN (m,n,p,imp) specifies the load impedance in ohms (ohm) units.
y = WGN (m,n,p,imp,state) resets the state of the RANDN.

You can also attach some of the iconic parameters after a numeric variable:
y = WGN (..., powertype) specifies the unit of P. Powertype can be ' DBW ', ' dBm ' or ' linear '. The linear strength (linear power) is measured in watts (Watt).
y = WGN (..., outputtype) specifies the output type. OutputType can be ' real ' or ' complex '.
2. AWGN: Adding Gaussian white noise to a signal
y = AWGN (X,snr) adds Gaussian white noise to the signal x. Signal-to-noise ratio snr is measured in db. The strength of x is assumed to be 0dBW. If x is a complex number, the complex noise is added.
y = AWGN (x,snr,sigpower) If Sigpower is a numeric value, it represents the signal strength in dBW, and if Sigpower is ' measured ', the function will measure signal strength before adding noise.
y = AWGN (x,snr,sigpower,state) resets the state of the RANDN.
y = Awgn (..., powertype) specifies the SNR and sigpower units. The powertype can be ' dB ' or ' linear '. If the powertype is ' db ', then the SNR is in db, and Sigpower is in DBW. If Powertype is ' linear ', then SNR is measured as a ratio, and sigpower in Watts

The use of WGN and AWGN functions of white noise in matlab