A Gaussian noise is a type of statistical noise in which the amplitude of the noise follows that of a Gaussian distribustion whereas additive white Gaussian noise is a linear combination of a Gaussian noise and a white noise (white noise has a flat or constant power spectral density).

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"Circular" means the variance of the real and imaginary parts are equal.

"White" refers to the fact that the power spectral density of the noise is flat across the whole frequency spectrum. This means that its autocorrelation is a Dirac-delta at t=0 (so its covariance matrix will show noise powers on the diagonal elements and zeros elsewhere).

"Gaussian" means the probability distribution of the amplitudes of the noise samples is Gaussian.

for a white noise the psd is flat i.e the distribution of energy over central freq is 1 and for gaussian noise as the name says the psd is normally distributed.

Gaussian noise is similar to white noise, but it falls within a narrower range of frequencies. In communications, it is produced by the movement of electricity through the line. You see and hear that when you have your television on an empty channel. Within photos and videos, Gaussian noise is in the form of random patterns, and this is what makes things look slightly blurry.